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72 / JOURNAL OF MANAGEMENT IN ENGINEERING / JULY/AUGUST 2000

PEER-REVIEWED PAPER: SPECIAL ISSUE ON LEARNING ORGANIZATIONS

BUILDING LEARNING ORGANIZATIONS IN ENGINEERINGCULTURES: CASE STUDY

By David N. Ford,1 Member, ASCE, John J. Voyer,2 and Janet M. Gould Wilkinson3

ABSTRACT: The ability of organizations to learn is critical for success. Implementing or-

ganizational learning in engineering cultures can be difficult due to a focus on technology

instead of people and imbalances among cultures within an organization. A project to trans-

form a medium-sized engineering organization into a learning organization is reported, and

the degree, nature, and causes of its success are evaluated. An implementation team developed

skills in five disciplines of a learning organization. However the underlying organizational

learning concepts were not embraced by the organization at large or incorporated into regular

operations. Success was constrained by the organizations ability to share and utilize the

knowledge acquired by the implementation team to generate organizationwide commitment

to organizational learning. The dominance of the engineering culture and the lack of orga-nizational learning infrastructures and development process experimentation suggest that or-

ganizations with a balance among cultures may be more likely to succeed than those domi-

nated by a single culture.

INTRODUCTION

Learning by organizations as well as their individual

members is critical for success in the future. The need

for learning increases as engineered systems grow in

complexity. Product and process complexity require spe-

cialization and approaches that integrate many different

interdependent aspects of development. This increasesinformation processing loads on developers and man-

agers and thereby retards organizational learning (Carley

1998). Therefore a primary constraint on improving

products and processes can be the ability of engineering

organizations to learn.

Operationalizing organizational learning in engineer-

ing-driven organizations is difficult (Roth and Kleiner

1996; Bohlin, n.d.). The fundamental structures, beliefs,

and actions of traditional organizations often differ sig-

nificantly from those necessary in a learning organiza-

1Asst. Prof., Dept. of Civ. Engrg., Texas A&M Univ., College Sta-

tion, TX 77843-3136. E-mail: [email protected]. Prof. of Business Admin., School of Business, Univ. of

Southern Maine, 96 Falmouth St., P.O. Box 9300, Portland, ME

04104-9300. E-mail: [email protected] Author and Consultant, 75 Oak St., Wellesley, MA

02181; formerly, Assoc. Dir. of the Organizational Learning Ctr., Mas-

sachusetts Inst. of Technol., Cambridge, MA. E-mail: jgould@post.

harvard.edu

Note. Discussion open until January 1, 2001. To extend the closing

date one month, a written request must be filed with the ASCE Man-

ager of Journals. The manuscript for this paper was submitted for

review and possible publication on December 14, 1999. This paper is

part of the Journal of Management in Engineering, Vol. 16, No. 4,

July/August, 2000. ASCE, ISSN 0742-597X/00/0004-00720083/

$8.00 $.50 per page. Paper No. 22172.

tion (Senge 1990). Actions that intuitively would be

expected to facilitate a transformation can be counter-

productive. For example, increased communication can

inhibit instead of facilitate organizational learning (Ar-

gyris 1994). The balance among cultures within an or-

ganization can be important in determining the organi-

zations learning needs and how learning skills can be

developed. Organizational culture manifests itself in

deep tacit assumptions, espoused values, and day-to-day

behavior (Schein 1985). Schein (1999) distinguished

among three organizational cultures: operational, exec-

utive, and engineering. Operational cultures use the in-

dustrys core technologies to produce the organizations

product. The organizations executive culture uses peo-

ple to indirectly control the organization, and the engi-

neering culture applies the technologies that underlie the

organizations work (e.g., designing computer chips or

applying construction processes). Schein (1999) argued

that a lack of alignment among these three cultures

within an organization can explain failures to learn. Inthis paper we use the imbalance of cultures in an engi-

neering organization to explain the failure of a project

to build a learning organization.First, the problem of building learning organizations in

engineering cultures is clarified. In the following section

an organizational learning project in an engineering or-

ganization, in which the writers participated as field re-

searchers, is reported. The success of the project is as-

sessed. That assessment is then used as the basis for

considering possible explanations for the projects limited

success. This paper concludes with a discussion of the

limitations of the work and future research opportunities.


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JOURNAL OF MANAGEMENT IN ENGINEERING / JULY/AUGUST 2000 / 73

CHALLENGES IN BUILDING LEARNINGORGANIZATIONS

Although the literature on organizational learning

reaches back several decades (Argyris and Schon 1978),

the perception that organizational learning skills are crit-

ical to success have been developed widely only more

recently. The Fifth Discipline, The Art & Practice of the

Learning Organization, a book by Senge (1990), was

particularly influential in the growth of this awareness(Crainer 1998), including in the organization studied

here. According to Senge, a learning organization has

competencies in five disciplines: personal mastery,

shared vision, mental model skills, team learning, and

the use of systems thinking. Personal mastery is the de-

fining and creative pursuit of excellence by individuals,

largely through visioning and actions consistent with that

vision. A shared vision describes the organization that

its participants desire to create as a tool for guiding and

driving change. Mental model skills expose beliefs and

assumptions that underlie actions and often defeat well-

intentioned policies. The same skills are used to create

new and more effective processes. Team learning is thedevelopment of new organizational knowledge through

the innovative coordinated action of groups of individ-

uals. Senge considered systems thinking to be the linch-

pin of organizational learning because of its ability to

describe and explain dynamic complexity through an ap-

preciation of the structural feedback inherent in systems.

Researchers have subsequently elaborated on the mean-

ing of these five disciplines [e.g., Senge et al. (1994)].

The literature describes organizational learning at two

levels: (1) Individual areas of competence (e.g., the five

disciplines); and (2) a phenomenon of the organization

as a whole, as in Senges definition of learning as ex-

panding the ability to produce the results we truly wantin life. (Senge 1990, p. 142).

Few general or widely applicable principles have been

developed and rigorously tested for building learning or-

ganizations. Research has concentrated on describing

learning organizations and on individual customized im-

plementations of organizational learning concepts and

tools in a variety of organization types. This work has

demonstrated the customized nature of transformations

into a learning organization. Our work does not refute

this lesson. The case studied here is similar to previous

projects in its customization of organizational learning

to the specific organization. However, research into the

roles of culture in organizations (Schein 1985) and the

thinking processes of engineering and related fields in

particular (Rowe 1991; Schon 1983) suggest that engi-

neering organizations may share a set of pitfalls and ef-

fective tools and methods for developing learning skills.

These valuable guidelines are not currently available. We

seek to improve our understanding of the processes that

managers and engineers in engineering cultures can use

to effectively build a learning organization. We address

this gap by investigating the degree, nature, and causes

of success in building a learning organization in one en-

gineering organization. This assessment provides a basis

for reflection on the role of an engineering culture on

building learning organizations.

CASE BACKGROUND

Computer Chips International is a large manufacturer

of semiconductors. The fieldwork for this research took

place at Computer Chips Internationals Seaport plant,

located far from corporate headquarters. The Seaport fa-

cility was started in the early 1960s. The plant has hadthree different owners. The Seaport facility initially was

a computer chip fabrication facility. At the time of this

research, it also did significant research and development

for the Data Shaping Division (DSD), which is the dom-

inant division housed at Seaport and the organization

studied in this research. Actual names of the company,

departments, and locations have been disguised to pro-

tect confidentiality.

The DSD is driven by its development of new prod-

ucts and redesign of its existing products to meet new

market needs. Therefore, the engineers in the DSD play

a commanding role in the organization and determine its

dominant culture. The technology of semiconductor de-sign and fabrication evolves quickly, and the challenges

of harnessing the latest technology in faster, smaller, and

more powerful chips is a common topic of discussion at

the DSD. The DSD has developed a distinctive compe-

tency in the design and fabrication of low-priced, com-

moditylike computer chips. Each of Seaports three own-

ers has manipulated the size of Seaports labor force in

response to the industrys cycles of growth and shrink-

age. At the time of the project, the labor force at Seaport

was approximately 1,800, substantially below the peak

number of about 3,000. These fluctuations have had a

powerful effect on the culture of the Seaport facility and,

as will be described, on the implementation of organiza-

tional learning. The culture of the DSD was distinctively

different from corporate headquarters. The distinctiveness

of the culture is heightened by Seaports location. The

Seaport area has a very attractive quality of life. It has

substantial natural beauty that is enhanced by a relatively

low cost of living, good schools, and reasonable access

to major urban centers. A major issue for Seaports work-

ers is that there are no other semiconductor facilities

within hundreds of miles of Seaport. A layoff from the

Seaport facility means an undesirable move to a distant

part of the country. The effect has been to create a very

strong work ethic based partly on a desire to avoid lay-offs. Voluntary turnover is lower at Seaport than anywhere

else in the semiconductor industry. Many people have

been working there more than a decade, which is signif-

icantly longer than average for this industry.

The DSD is dominated by its engineering culture.

Schein (1999) characterized engineering cultures as be-

ing driven by optimism based on science and available

technology, and because the culture takes form in asser-

tive action for improvement (a can-do attitude). En-

gineers are stimulated by puzzles and problems to be

overcome through the pragmatic design and construction

of useful products and outcomes. According to Schein


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1999, p. 13), Engineers recognize the human factor and

design for it, but their preference is to make things as

automatic as possible. In their efforts to develop effec-

tive and efficient products, engineers prefer to design

humans out of systems rather than into them. The culture

of the DSD is consistent with Scheins characterization.

Of particular significance to this work, DSDs engineer-

ing culture was pervasive throughout the organization.

The DSDs upper management consisted primarily of en-

gineers, most who had been promoted from within Com-puter Chips International and strongly reflected their

prior engineering culture in their management styles.

The DSDs engineering culture also dominated opera-

tions, partially due to the regular and frequent introduc-

tion of new technologies (developed within the engi-

neering culture) into operations in the form of new and

improved products.

In the early 1990s Computer Chips International and

the DSD felt increasing competitive pressure to improve

their effectiveness in developing new products. The DSD

responded with a multitude of improvement programs.

These programs resulted in process improvements such

as the development and documentation of a standardproduct development process and its products, the defi-

nition and measurement of development performance

(e.g., development project durations, called cycle time),

and process changes to reduce the durations of individ-

ual development project phases (e.g., product definition

and design). As part of these improvements, DSD man-

agement formed a team of seven people in the fall of

1993 to investigate new ways to reduce cycle times. De-

spite initial success in reducing cycle times, improve-

ment slowed and then stopped. Projects to reduce the

durations of individual phases only increased the dura-

tions of other phases, resulting in no net cycle time im-

provement. The interphase effects of improvement proj-

ects using a reductionist approach suggested that a

systemic response was required for further improvement.

Based on their preliminary work, the group decided to

assess how the concepts and tools of learning organi-

zations could enhance the effectiveness of product de-

velopment. They concluded that transforming the DSD

into a learning organization was required to substantially

reduce the cycle time. The team set a primary objective

of implementing organizational learning in a single prod-

uct team as a prelude to implementation throughout the

DSD. The seven people and the three members who

joined them later are referred to as the ImplementationTeam. To support the organizational learning project the

Implementation Team formed an alliance with the Or-

ganizational Learning Center at the Massachusetts Insti-

tute of Technology. Three researchers from the Organi-

zational Learning Center (the writers) worked with the

seven DSD members to develop an effective means of

transforming the DSD into a learning organization by

implementing organizational learning in a subunit of the

DSD. The role of the research center members was to

facilitate the Implementation Team in three areas: (1)

The design of a project to implement organizational

learning; (2) assessment of learning; and (3) the assess-

ment of DSD learning about learning. The first objec-

tives of the team were to develop their own organiza-

tional learning skills while transforming a small portion

of the DSD into a learning organization. The team fo-

cused their efforts on the Progressive Logic Department

(PLD), a subunit of the DSD that included some mem-

bers of the Implementation Team. The PLD had approx-

imately 100 engineers working in five units, four on var-

ious aspects of product development and one performing

a support function. This research focuses on the imple-mentation of organizational learning in the Implemen-

tation Team and PLD.

In the spring of 1996 Computer Chips International

began a reorganization that resulted in portions of the

Seaport facilitys being spun off in a management buyout

and the remaining operations being restructured. As a

result most members of the Implementation Team were

transferred to the spin-off organization, which acquired

the DSD as part of the buyout. Although some individual

members of the team continued work to build a learning

organization, activities were sharply curtailed when the

reorganization began, focusing team members intently

on job security issues and effectively ending the learningorganization project.

RESEARCH METHODS

The research gap was addressed through a revelatory

case study. Of the ten challenges to building learning

organizations identified by Senge et al. (1999), only

those relating to culture dominate this case (with some

related influences by diffusion and assessment issues). In

particular the four resources that Senge et al. (1999)

identified as potential constraints (assistance, leadership,

time and, upper management support) were adequate.

The DSDs upper management supported the project to

become a learning organization. Executives and devel-

opers specifically and repeatedly voiced the need for

learning. As a part of scanning to compare the DSD with

its environment, the Implementation Team interviewed

people from management, marketing, design, quality as-

surance, applications, and operations (Computer Chips

International 1994). When asked to identify aspects of

DSD that inhibit product development, the managers, de-

signers, and quality assurance engineers identified learn-

ing most often, and the other three domains listed related

topics (e.g., improving feedback and teamwork) as im-

portant. Management support extended beyond verbalsupport. The DSDs executives participated in transfor-

mation meetings and activities and provided adequate

resources. Financial support included research funds for

the inclusion of external consultants and researchers in

the project (including the writers) and time for organi-

zation members who were central to the DSDs primary

operations to participate in the project. Significantly,

support was considered more than adequate by the Im-

plementation Team.

Our case is revelatory in that most of the factors used

to explain success or failure in organizational learning

projects had little effect. The relative freedom of the


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project from a majority of the identified barriers to build-

ing a learning organization allows us to effectively ig-

nore them as potential explanations of project success or

failure. This and the dominance of an engineering cul-

ture provide a unique opportunity to investigate how en-

gineering cultures impact the effectiveness of becoming

a learning organization.

Data Gathering

The Implementation Team and researchers collectedthe data using an action science approach in which re-

searchers are also participants in the system being stud-

ied (Argyris and Schon 1978). Together the team and

researchers created a mix of inside and outside perspec-

tives and expertise. Members of the implementation

Team were from design, testing, marketing, and human

resources. The researchers represented expertise in or-

ganizational learning, system dynamics (Forrester 1961),

qualitative field research, and organizational theory. In

preparation for data gathering, all members of the Im-

plementation Team were trained in qualitative data gath-

ering, primarily the recording of field notes, qualitative

interviewing, and participant observation (Glaser andStrauss 1967; Glaser 1978; Lofland and Lofland 1984;

Taylor and Bogdan 1984). The Implementation Team

and others also went through a 5-day training course in

the fundamental concepts, tools, and methods of orga-

nizational learning as defined by Senge (1990). Five

members of the Implementation Team and one re-

searcher became active interviewers and participant ob-

servers in organization meetings.

As a part of the project, 12 members of the DSD were

interviewed by the researchers, and 40 members of PLD

were interviewed over a period of 6 months by four

members of the Implementation Team. In semistructured

interviews, respondents who represented a broad cross

section of PLD were asked to identify and reflect on

portions of the DSD that enabled and inhibited new

product development. Also, an average of two meetings

per week were observed by two members of the Imple-

mentation Team and a researcher. The meetings were of

various typesplanning, technical, and management

cutting across all five units of PLD. Finally, the Imple-

mentation Team kept field notes on ongoing interactions

that they had with others in PLD and the DSD.

Data Checks

Guba and Lincoln (1982) offered criteria for evaluat-ing and strategies for assuring the rigor of qualitative

research projects. They argued that data from any sci-

entific inquiry must have four characteristics: (1) Internal

validity (truth value); (2) external validity (applicability

or transferability); (3) consistency, reliability, or depend-

ability; and (4) objectivity. Several steps were taken to

improve data and analysis reliability. Triangulation in the

form of multiple data sources (interviews, direct obser-

vation, and participant observation), tapped by multiple

members of the Implementation Team and researchers,

improved internal validity and objectivity by enriching

the teams constant dialogues over reliability and objec-

tivity. Credibility was fostered by persistent engagement,namely, the Implementation Teams longevity with and

extensive local knowledge of the site and the re-searchers persistent and extended (over several years)close involvement with and resultant knowledge about

conditions at the site. Transferability was strengthenedby gathering data from over 40 members of a rich fieldsite that was very embedded in the real work of the

semiconductor industry. Finally, objectivity was im-

proved by training Implementation Team members andresearchers in qualitative data collection methods, to en-

sure that data were gathered in as verbatim a manner aspossible, and in qualitative data analysis, to improve ob-

jectivity and increase triangulation of evaluation acrossmultiple analysts with different perspectives of the is-sues.

Data Reporting and Analysis

To structure the many and various parts of the project,we sorted the work on each of the five disciplines into

four categories: awareness of organizational learning is-sues and the practices, products, and infrastructures for

organizational learning. Each category describes an im-portant kind of data about the project. The discussion oforganizational learning topics prior to or during the proj-

ect demonstrates an awareness and focus on certain as-pects of the organization and its learning needs. Orga-nizational learning practices demonstrate conscious

efforts to develop competence in specific skills. Productsdemonstrate results of practices, suggesting which prac-tices and disciplines had potential for generating change.

Organizational learning infrastructures demonstrate theexistence or development of support systems for incor-porating organizational learning into the DSD culture

and perpetuating organizational learning.

Two units of analysis have been used to evaluate theproject. Each unit of analysis has a separate set of cri-teria. First, competence in the development of skills ineach of the five disciplines identified by Senge as critical

for organizational learning are assessed based on criteriadescribed in Senge (1990) and expanded by Senge et al.(1994). The primary reason for selecting these criteria is

that they were the definition and description of organi-zational learning adopted by the Implementation Team.Therefore, the project objectives and evaluation criteria

are very closely aligned. The second unit of analysis isthe project as a whole. An evaluation of the five disci-

plines individually does not provide an overall assess-

ment of the organizations success at becoming a learn-ing organization. To do so we extend the use of

knowledge acquisition, knowledge sharing, and knowl-edge utilization as critical steps in organizational learn-ing by Nevis et al. (1995) for use as an assessment tool.

Finally, the results of the evaluations at each unit of anal-ysis are compared for consistency to assess the degree,nature, and causes of project success.

FINDINGS

We grouped our findings according to the five learningorganization disciplines. However the five disciplines are


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not mutually exclusive, and many observations could be

described as part of several disciplines. Findings have

been located based on the importance of specific prac-

tices, products, and infrastructures to specific disciplines

as described in the literature, and our assessment of the

discipline in which the competence was most affected.

Personal Mastery

The members of the Implementation Team perceived

personal mastery as low in the DSD prior to the project.Creativity in problem solving was low, and people con-

sistently believed and described that people other than

themselves were responsible for the challenges faced by

the DSD (a they did this to us mentality). Several

members of the Implementation Team saw personal mas-

tery as one of the most interesting aspects of the project

because it facilitated their personal as well as profes-

sional development. The number of events and practices

designed to improve personal mastery indicate the level

of skill developed. The Implementation Team held a

meeting very early in the project at which they described

their personal visions, and members subsequently re-

ported informally on their private attempts to developpersonal mastery skills (largely personal visioning).

These personal visions often included deep personal is-

sues such as lifetime goals and the desire by one Imple-

mentation Team member to have the DSD be an ex-

tended family. As a part of a larger Computer Chips

International effort to promote change, participants in

small group meetings drew illustrations of their personal

visions. One result of personal mastery work was a tran-

sition by Implementation Team members away from

seeking external causes for challenges to identifying in-

ternal causes and thereby potential high leverage points

for change. Team members described this change of ap-

proach as recognizing that there is no they that is the

cause of their problems but that the fundamental drivers

of DSD behavior and performance are within the DSD.

Although individual achievement was rewarded in the

DSD, few infrastructures for personal mastery develop-

ment were found.

Shared Vision

The DSD believed that it needed a shared vision to

become a learning organization, and the DSD was aware

of the challenges in developing shared visions. Devel-

oping shared visions received an enormous amount of

time and effort across the organization. Before the proj-ect began, members of the DSD and others throughout

Computer Chips International participated in multiple

sessions led by professional facilitators to develop, ar-

ticulate, and describe a corporate vision. Physical prod-

ucts of Computer Chips Internationals visioning work

were evident throughout the Seaport facility. A gray

stone monument engraved with the vision statement was

prominently displayed in the central building and be-

came affectionately known as the gravestone. Profes-

sionally designed, illustrated, and produced banners de-

picting the vision aggregated from the corporationwide

effort hung in many places throughout the facility. Feed-

back was solicited from the DSD on the corporate vision,

although no changes resulted from these comments. De-

veloping a shared vision was also seen as important by

product groups. For example, one team developed a

team vision and their road map (plan) for reaching it.

Discussions revealed a common language and under-

standing of the DSD objectives throughout the organi-

zation regardless of their level of participation in other

organizational learning activities.

Commitment to the DSDs vision was weaker than thevision was clear. This was due primarily to large pres-

sures for short-term financial performance. One engineer

reported that there was little commitment to long vision

when faced with short goals. Process and organizational

challenges also weakened commitment to implement the

shared vision. For example, PLD faced narrow market

windows, a steep learning curve for developing their

products and team goals, roles, and interdependencies

that were not clear in addition to unclear definitions of

success that were not shared. Despite limited commit-

ment the visual descriptions of the DSDs shared vision

created a strong support structure that reinforced the use

of the visions concepts (e.g., being customer focused)and language (e.g., seeking to produce customer

delight). This sustained the use of the shared vision as

a communication tool within the DSD and caused it to

become an integral part of the DSD culture.

Mental Models

The Implementation Team considered developing their

own mental model skills to be one of the most important

parts of organizational learning. Therefore this discipline

received more focus and effort than most. The Imple-

mentation Team frequently and regularly used a variety

of tools recommended in the literature to develop mental

model skills including individual and group causal loop

diagramming (Goodman 1974; Richardson and Pugh

1981); the ladder of inference (Ross 1994; Argyris

1990); balancing reflection, inquiry, and advocacy (Ross

and Roberts 1994); the left-hand column (Ross and

Kleiner 1994); and hexagons (Hodgson 1992).

The Implementation Teams work in developing their

mental model skills produced an increased awareness of

the DSDs current reality. Consider the omnipresent fear

of job loss and subsequent forced relocation away from

a community widely considered very desirable. One soft-

ware engineer on the Implementation Team reported that

When lay-offs come, he who cranks the most data sur-vives and that Fear is the driving force through this

organization. No one wants the in-basket empty re-

ported another engineer. A contributing factor in this fear

was that many engineers saw themselves as currently

employed but not necessarily valuable to other firms in

the event of losing their position in the DSD. The fear

of job loss strongly affected the developers decisions,

actions, and commitment to organizational learning, as

can be seen in one engineers declaration that Until I

know I have a job I will not work on this [organizational

learning]. This mental model caused development at

the DSD to be regularly disrupted by rumors of job-


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FIG. 1. Example Organizational LessonDilemma of Outsourcing Failure Analysis

threatening changes in Computer Chips International or

the DSD. Working with mental models helped these is-

sues to become clearer to the Implementation Team.

Mental model work also revealed paradoxes faced by

DSD due to different timescale perspectives. A simple

example is that reducing cycle times reduces job security

in the short term by increasing the DSDs development

capacity relative to demand but that not reducing cycle

time reduces job security in the long term by reducingthe DSDs competitiveness.

Systems thinking was frequently integrated into work

with mental models. The most common tangible prod-

ucts of mental model work were causal loop diagrams

with textual descriptions of DSD mental models and an

organizational lesson learned. For example, Fig. 1 and

the description that follows were generated by a member

of the Implementation Team based on field data and

mental model work using causal loop diagramming (a

systems thinking tool) to analyze the DSDs outsourcing

of prototype failure analysis.

After receiving yet another inconclusive FA [fault

analysis] report the development engineers felt that

they had to outsource the FA work to get their product

line up and running. These systems loops seem to in-

dicate that the logic used by the development engineers,

even though intuitively correct initially, might very well

have long-term problems, and the solution might in fact

exacerbate the original problem: the abilities of the FA

group might deteriorate over time.

Therefore, the development engineers decided that

they might have to outsource temporarily, but that there

is higher leverage in improving the local FA so that it

can handle any request quickly and deliver quality re-

ports that enable the development engineers to develop

a corrective action plan so that they would have a man-

ufacturable product line.

Team Learning

A survey of learning styles indicated that skill devel-

opment in PLD was mostly individual and not as a group

(Computer Chips International 1994), suggesting the

need for developing team learning skills. Although es-

poused as a desired skill by the Implementation Team

and PLD management, little evidence of a strong aware-

ness of a need or focus on team learning was found.

PLD personnel attended short courses in Human Dynam-

ics (Seagal and Horne 1997) to improve their interaction

skills and held team building (versus team learning) ex-

ercises. The Implementation Team initiated the use of

dialogue sessions in the DSD. Participation by Imple-

mentation Team members was high, and attendance by

others in PLD was significant. But attendance dwindled,

and sessions became more sporadic when benefits were

not as apparent and quick as desired. Cross functionaldevelopment teams were a firmly established part of the

organizational structure prior to the project, but PLD ex-

perienced significant fragmentation among team mem-

bers.

Two attempts to create infrastructure for team learning

were made near the end of the project. Weekly meetings

for cross-team learning were begun but interrupted by

the reorganization and not continued. More significantly,

PLD colocated the developers for a specific product into

a single enclosed area with close proximity of developers

and a common space for formal and informal interaction.

Colocation caused communication within PLD to occur


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faster but not better. Conflicts broke out among function-

based subcultures within the colocated PLD team (chip

engineers, software developers, hardware developers,

etc.), and the group was physically disaggregated.

Systems Thinking

Early in the project (October 1993) a member of the

Implementation Team observed that We [people in the

DSD] have words to describe the pieces. We dont have

words to describe the system. The ImplementationTeam considered developing competence in systems

thinking to be a major activity and interest. Systems

thinking activities included managing a relatively simple

but dynamic system through simulation (Sterman 1989),

causal loop diagramming sessions, workshops with en-

gineers to elicit and articulate important relationships

that link product development processes (Ford and Ster-

man 1998a), and the application of the system dynamics

methodology to model a PLD development project (Ford

1995).

An example of the development of systems thinking

skills is related to the transition from a focus on external

causes of problems (they) to a There is no theyperspective described in the Personal Mastery section

above. The new perspective resulted in one member of

the Implementation Team recognizing that his chronic

overestimation of cash needs to protect his departments

budget contributed to the DSDs management mandating

extraordinary measures to generate cash and that he was

a part of the system causing the problem instead of the

management (they) who imposed unreasonable ac-

tions to generate cash. This team member was deeply

shaken by the realization that he partially caused the

behavior he very much wanted to prevent. The research-

ers also produced systems thinking products by reflect-

ing for several months after the project and developing

lessons into publications directed toward other systems

thinking researchers (Ford and Sterman 1998a,b; Voyer

et al. 1997) and practitioners (Gould et al. 1998). Despite

a significant amount of activity and practice for devel-

oping systems thinking skills, no infrastructures were put

in place for this discipline.

ANALYSIS OF THE LEARNINGORGANIZATION PROJECT

In this section, we analyze the organizational learning

project at two levels of aggregation as suggested by the

literature. First, we assess the competence developed in

each of the five disciplines using criteria in the literature

with a focus on the standards used by those in the case.

Then, we assess the project as a whole using a systems

thinking perspective of existing criteria.

Personal Mastery

Senge (1990, p. 141) called personal mastery the dis-

cipline of personal growth and learning and described

it as a deeply inquisitive seeking after a personal vision.

Some (perhaps half) of the Implementation Team dis-

played characteristics suggesting active work in this dis-

cipline. This included a strong sense of purposeful vision

behind their actions balanced by an improved perception

of their current reality (although this remained a chal-

lenge throughout the project). Holding these two images

simultaneously creates the tension that drives individuals

toward their deep goals. Implementation Team members

displayed strong interest in and dedication to improving

DSD product development and were deeply inquisitive.

This took form in their perseverance and persistence in

seeking to understand and implement a learning orga-nization and their improved skills in honest communi-

cation. The Implementation Team and PLD members

were, almost without exception, highly motivated and

intelligent professionals driven to improve DSD regard-

less of the project. The personal mastery work may have

facilitated this drive, although the extent to which these

characteristics can be attributed to the organizational

learning project cannot be easily or exactly determined.

Some aspects of personal mastery caused difficulty for

the Implementation Team and the DSD in general. Peo-

ple found it difficult to work in concert with the forces

of change instead of working against those forces and

were unable to perceive and use forces of change to helpthem implement organizational learning. The DSDs in-

tense focus on metrics and short-term performance made

it very difficult to focus on personal visions. One man-

ager who was not a member of the Implementation Team

said We will not let cycles of learning slow down our

cycle time. Senge (1990) considered the ability to focus

on visions instead of performance metrics as a corner-

stone of personal mastery. Performance reviews were

redesigned to include peer reviews and to assess perfor-

mance based on technical expertise as well as manage-

ment and communications expertise near the end of the

project, which can facilitate the development of personal

mastery (Roberts 1994). However, these changes were

not implemented.

The Implementation Team had a strong interest in per-

sonal mastery, but there was little interest or effort in

this discipline outside the team. Based on the minimal

evidence of personal mastery practices or products we

conclude that some members of the Implementation

Team developed some personal mastery skills but that

widespread competence in this discipline was not

achieved.

Shared Vision

The DSD developed a single vision that was sharedacross the organization. In addition, product groups

within the DSD developed shared visions that included

objectives such as shifting from commodity products to

more complex products. Smith (1994) described five

progressive stages in building a shared vision: telling,

selling, testing, consulting, and cocreating. Based on the

extensive collection of individual perspectives of the

corporate vision, Computer Chips International initially

attempted to use a cocreating approach in which neither

management nor engineers dominate and both collabo-

rate to build a single shared vision together. However

this degenerated into more telling when feedback on


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the initial description was ignored by corporate head-

quarters. Despite the imperfect implementation of the vi-

sioning effort, the process and significant resources over-

came major limits to the growth of shared visions such

as polarization, discouragement, and overselling by

managers (Senge 1990) and resulted in a single image

of the DSDs organizational objective.

Despite the DSDs contribution to developing a shared

vision there is no evidence that the shared vision fostered

the risk taking and experimentation suggested by Senge(1990). Nevis et al. (1995) and Dixon and Ross (1999)

identified an experimental mind-set as an important com-

ponent of organizational learning. They associated this

mind-set with the ability to play; to learn through fre-

quent small failures; and to perceive processes, policies,

and structures as unfinished attempts in a continuous se-

ries of trials. In the DSD, failure carried a very high

price, including an increased chance of job loss in the

inevitable next round of layoffs. Managements espoused

desire to become a learning organization was overshad-

owed by their actions, which showed an intolerance of

failure. The DSDs resulting inability to see their product

development operations as experiments limited the ben-efits of their shared vision.

Based on the substantial findings about the process

and products of DSDs visioning work, we conclude that

DSD was successful at developing and maintaining a

shared vision of what they wanted their organization to

become. But the risk averse culture prevented the gen-

eration of enough creative tension between the vision

and DSDs reality to realize the organizations objective

to become a learning organization.

Mental Models

The numerous products generated during the project

by the Implementation Team, which resulted from men-

tal model training, indicate improved competence in the

Implementation Teams skills in seeing and describing

existing mental models. Skills in designing and imple-

menting new mental models were developed to a lesser

degree. The frequent and regular use of many mental

model tools indicates that the Implementation Team in-

ternalized these concepts and developed significant com-

petence in their use. These practices resulted in changes

in the mental models of the DSD held by the Imple-

mentation Team, another indication of competence in

this discipline (Roberts 1994). However there is little

evidence of the development of significantly differentand operational mental models by those outside the Im-

plementation Team. This suggests that the they were un-

aware or unconvinced of the advantages of investing in

this discipline.

We conclude that the Implementation Team signifi-

cantly increased its skills in working with mental models

as a result of the project. These increased skill levels

produced new and improved mental models for these

team members. However improved mental model work

did not spread throughout PLD or the DSD. We therefore

assess that the implementation of the mental model dis-

cipline was a partial success.

Team Learning

Senge (1990) described team learning with three crit-

ical dimensions: (1) Participation of team members on

other teams; (2) insightful thinking about complex is-

sues; and (3) innovative coordinated action. There is ev-

idence of competence in two of these three dimensions.

Several Implementation Team members were part of

PLD, and team members throughout the DSD partici-

pated in multiple product teams and improvement pro-

grams. This demonstrates the existence of a potentiallyeffective infrastructure for spreading lessons learned by

one team to others. As a step toward developing skills

in insightful thinking about complex issues, engineers

held dialogue sessions (Isaacs 1993) to improve their

abilities to discuss and converse meaningfully. The Im-

plementation Team also attempted to discuss undis-

cussables, important topics that are so sensitive that

they are taboo, but experienced only limited success. For

example, job security fears were discussed (albeit usu-

ally superficially), but the widespread mistrust of upper

management by engineers was rarely mentioned. There

is little evidence of innovative coordinated action by the

Implementation Team or PLD. Additionally, little evi-dence was found of the application of team learning to

transfer lessons learned by one product team to other

teams. This suggests that team learning in the DSD was

limited in scope as well as depth. We conclude that the

Implementation Team and the DSD were primarily un-

successful at implementing team learning.

Systems Thinking

Systems thinking is the discipline that integrates the

other disciplines and a learning organization itself. The

Implementation Team developed their skills in seeing

DSD as a system instead of a set of loosely related parts.

This improved their competence in systems thinking, as

evidenced in changes in the language (Senge et al.

1994). New approaches to behavioral problems in the

DSD such as looking for causes of problems that are

separated in time and space from the problem behavior

also indicate competence. Some skills (e.g., describing

feedback structures) were developed more than others

(e.g., seeing and recognizing patterns in system behav-

ior). In general, the DSDs engineers continued to focus

on events such as specific management decisions and on

individuals to explain problems instead of system struc-

ture. Little competence was developed in recognizing

and accepting a worse-before-better behavior patternor seeing and waiting for delayed impacts to travel

through systems. Developing these skills was very dif-

ficult due to the intense focus on short-term results but

critical for changing how engineers saw themselves and

their environment. We conclude that the Implementation

Team developed significant competence in systems

thinking but that competence was not developed more

broadly. The project was partially successful at devel-

oping competence in systems thinking.

Our assessment of the development of competence in

the individual disciplines reveals that success varied sig-

nificantly across the five disciplines and among the Im-


9/12


FIG. 2. Design for Building a Learning Organization

plementation Team, PLD, and the DSD, with the Imple-

mentation Team developing their organizational learning

skills much more than the other groups. There was some

dissemination of learning activity in progress when the

project was interrupted but little evidence of broader

competence in the five disciplines. Although developing

competence in some of the disciplines in a few dozen

people over a few years appears slow, the speed of skill

development and dissemination is consistent with the ex-

perience of other organizations (Senge 1990; Senge etal. 1994).

Aggregate Assessment of Organizational

Learning Implementation

To evaluate the organizational learning project as a

whole, we extend three critical steps in organizational

learning as described by Nevis et al. (1995): knowledge

acquisition, knowledge sharing, and knowledge utiliza-

tion. The use of knowledge as the basis for judging or-

ganizational learning is supported by Senge equating

knowledge and learning (Meen and Keough, n.d.). Nevis

et al. (1995, p. 74) described knowledge acquisition as

the development or creation of skills, insights, relation-

ships; knowledge sharing as the dissemination of

what has been learned; and knowledge utilization as

the integration of learning so it is broadly available and

can also be generalized to new situations. We relate

these skills to organizational learning success with a sim-

ple causal loop diagram that describes the implicit design

of the organizational learning project at the DSD

(Fig. 2).

The project was designed to develop competence in

the five disciplines. These skills were intended to im-

prove the knowledge acquisition, sharing, and utilization

skills of the organization. Although all five disciplines

can facilitate each of the three knowledge activities, dif-

ferent disciplines are more effective at developing com-petence in specific knowledge activities due to the nature

of the discipline or the manner in which it is applied.

Personal mastery focuses on individuals developing and

maintaining a personal vision and a picture of current

reality, and it is therefore primarily concerned with ac-

quiring knowledge in the form of these two images.

Working with mental models requires two fundamental

skills: reflection (slowing thinking to increase aware-

ness) and inquiry (conversations for sharing views).

Therefore developing mental model skills primarily sup-

ports knowledge acquisition through reflection and

knowledge sharing through inquiry. Team learning sup-

ports both knowledge sharing through methods such as

dialogue (Isaacs 1993) and the development (acquisi-

tion) of group knowledge. Shared vision primarily sup-

ports knowledge sharing, and, consistent with its inte-

grating role, systems thinking supports all three


10/12


knowledge activities. The individual disciplines and

links are not shown in Fig. 2 between competence in

the five disciplines and the three types of knowledge

skill for clarity.

Knowledge acquisition, sharing, and utilization skills

are necessary but not sufficient in isolation to build a

learning organization. Knowledge sharing requires both

sharing skills and knowledge to be shared. Therefore

knowledge acquisition skills must have been success-

fully applied to create organizational knowledge prior toknowledge sharing. Similarly, knowledge sharing skills

must be applied to disseminate knowledge before knowl-

edge utilization skills can be applied to the shared

knowledge. As utilized knowledge improves perfor-

mance and those improvements are recognized as the

results of organizational learning, they increase the com-

mitment of the organization and its individuals to orga-

nizational learning, although this response is often de-

layed. This increases the effort applied to implementing

organizational learning. Repeated cycles around the

three reinforcing feedback loops in Fig. 2 are intended

to continuously strengthen the building of the learning

organization. The unrealistic absence of balancing loopsin the project design shown in Fig. 2 is consistent with

the mental models of the Implementation Team and

PLD. [For additional examples and discussion, see Voyer

et al. (1997) and Ford (1995).]

We used the development of knowledge acquisition,

sharing, and utilization skills to assess the project. The

Implementation Team was most successful in the shared

vision and mental model disciplines. These developed

their knowledge acquisition skills most and sharing skills

to some degree. The numerous descriptions of their les-

sons demonstrate that they successfully applied knowl-

edge acquisition skills to generate new insights about the

DSD and its operations. However a common weakness

across the disciplines was a lack of learning and infor-

mation infrastructures that could have facilitated the dis-

semination and utilization of organizational lessons and

skills (Senge et al. 1999). Therefore the Implementation

Team was unable to share knowledge significantly be-

yond their own group. They also had little success in

utilizing the knowledge that they acquired and shared

within the Implementation Team to improve the DSDs

operations. This identifies knowledge sharing across

teams and knowledge utilization as the primary con-

straints on project success.

If the DSD had been able to wait for and perceive thebenefits of the Implementation Teams learning work,

broader commitment might have developed. The litera-

ture (Senge et al. 1999) and previous organizational

learning building experience (Roth and Kleiner 1996)

indicate that patience is needed before significant im-

provements due to organizational learning can be rec-

ognized. The pressure on the Implementation Team to

quickly produce performance improvements that were

measurable with existing metrics of the DSD was in di-

rect opposition to this need and the worse-before-better

concept of systems thinking. The Implementation Team

was aware of the threats of operational improvements

being out of phase with learning and assessment but

were unable to address them successfully. This limited

the growth of commitment to organizational learning and

the development of a learning organization to the Im-

plementation Team.

DISCUSSION

We next propose and evaluate three hypotheses that

can jointly but not individually explain the projects fail-

ure to transform the DSD into a learning organization.The first hypothesis is that the lack of an experimental

mind set in the DSDs engineering culture prevented or-

ganizational learning. Organizational learning research-

ers have identified experimentation and risk taking as

important activities in developing a learning organization

(Senge 1990; Nevis et al. 1995). This mind-set is needed

to generate the many learning cycles necessary to ac-

quire, share, and utilize new organizational knowledge.

A survey of PLD learning styles revealed a lower than

average self assessment of the experimental mind-set

(Computer Chips International 1994), confirming the

low rate of experimentation with development processes.

This can be understood in the context of the culture ofhigh pressure for fast improvement and low perceived

job security, which caused experiments that fail (i.e.,

did not generate immediate improvement) to be expen-

sive for the experimenter. But the lack of experimenta-

tion can only partially explain the projects failure based

on the evidence that knowledge was acquired by the Im-

plementation Team by other means such as environmen-

tal scanning. The lack of an experimental mind-set is a

contributing but not critical factor in explaining the proj-

ects failure.

The second hypothesis is based on the three corner-

stones in the architecture of a learning organization sug-

gested by Senge (1994): (1) A set of guiding ideas; (2)

theory, methods, and tools; and (3) innovations in infra-

structure. The DSD developed and articulated guiding

ideas in their organizations vision. The Implementation

Team strongly believed in the principles of the learning

organization. The DSD also had ample theories, meth-

ods, and tools to build a learning organization. Many of

the tools and methods specifically identified in the lit-

erature for the development of organizational learning

were used over multiple years in the DSD with theoriesto support the use of each. But the DSD and the Imple-

mentation Team were very weak in developing infra-

structures for organizational learning. Few structures ofan organizational or physical nature were installed and

successfully used during the project. Senge (1994, p. 37)warned that Without innovations in infrastructure, in-spiring ideas and powerful tools lack credibility . . .

and that therefore Changes cannot take root and be-come part of the fabric of organizational life. Learningis left to chance. However, we suspect that success

must be experienced earlier than in the case studied toinstitutionalize learning infrastructures. Weak learninginfrastructures are a strong contributing factor but do not

fully explain why organizational learning was not dis-seminated successfully.


11/12


Our third hypothesis is grounded in the overwhelming

dominance of the DSDs engineering culture. Scheins

(1999) characterization of engineering cultures as being

less adept at designing solutions which include people,

suggests an inherent weakness in engineering cultures

for building learning organizations. The DSDs upper

management also behaved as an engineering culture, re-

sulting in the Implementation Team developing some of

the characteristics of an executive culture. The Imple-

mentation Team could have but was prevented from pro-viding the needed focus on designing people into control

systems. This is consistent with Scheins (1999) descrip-

tion of different cultures that contribute different, valu-

able perspectives of the organization. According to this

hypothesis, the DSDs engineering culture so strongly

dominated the organization that it proved impossible for

the Implementation Team to penetrate its resistance to

organizational learning. The dominance of the engineer-

ing culture, its risk averse nature, and the general anxiety

concerning job security at the site tended to isolate the

Implementation Team. This reinforced the threats posed

by organizational learning as perceived by the engineer-

ing culture and further increased resistance.In summary, we hypothesize that the project had lim-

ited success because the dominant engineering culture

successfully resisted the efforts of the Implementation

Team, acting as an ad hoc executive culture, to dissem-

inate organizational learning and that the resistance was

facilitated by the lack of organizational learning infra-

structures and the high cost of development process ex-

perimentation. The DSDs organizational learning proj-

ect may have experienced more success if (1) project

participants had recognized and countered the negative

effects of their dominant engineering culture; (2) infra-

structures for organizational learning had been devel-

oped; and (3) development process experimentation had

been allowed and practiced.

CONCLUSIONS

We have identified a case in which cultural issues

were critical to successfully building a learning organi-

zation. A project to transform a portion of a medium-

sized semiconductor firm into a learning organization

was described in terms of competence in five disciplines

of a learning organization. By assessing competence in

individual disciplines and the project as a whole, knowl-

edge sharing and utilization skills were identified as con-straints on project success. We argue that the dominance

of the engineering culture and lack of infrastructure and

experimentation can best explain the behavior of the

project. This suggests that engineering organizations

with balanced cultures may be more likely to succeed in

building learning organizations than those dominated by

any one of the executive, engineering, or operational cul-

tures.

This research had identified a balance among organi-

zational cultures as an important factor in building a

learning organization. The dominance of an engineering

culture, missing or weak infrastructures for organiza-

tional learning, and failures to experiment with devel-

opment processes have been identified as important con-

straints on building learning organizations. By relating

the five learning organization disciplines to project suc-

cess through knowledge acquisition, sharing, and utili-

zation skills we have provided a tool for organizational

learning project analysis. Learning organization imple-

mentation has been identified as an aspect of organiza-

tional learning theory needing additional research.

For practitioners, our work has identified culturaldominance as one way that engineering cultures can

limit project success. Our results suggest that managers

of engineering organizations that are attempting to be-

come learning organizations should assess the relative

influence of the cultures within their organizations and

design means for each culture to contribute to the trans-

formation. More generally, managers can identify and

utilize the strengths and weaknesses of their specific cul-

tures to design more effective learning organization proj-

ects.

The limitations and findings of our research suggest

potentially valuable areas for future research. Our work

was limited to one case study. Future research can im-prove external validity by comparing our results with

other organizational learning case studies, particularly

those in engineering dominated cultures. Our work iden-

tifies the development of knowledge skills and imple-

mentation methods as important areas for future orga-

nizational learning research. The relationship among

organizational learning methods, knowledge skills, and

project success is another potentially fruitful area for ad-

ditional research. Improved understanding of the rela-

tionship between organizational culture and learning can

improve the building of learning organizations.

ACKNOWLEDGMENTS

The writers thank the members of the DSD Imple-

mentation Team for their time and commitment to the

project and to Massachusetts Institute of Technologys

Organizational Learning Center for financial support.

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