Organisational structureneed to analyse how an organisation can maximize and sustain value from having a PMO in place.

PAPERS
February 2013 ■ Project Management Journal ■ DOI: 10.1002/pmj 59
INTRODUCTION ■
T
he organizational phenomenon of the project management office
(PMO) keeps the interest within the project management research
field. An indicator of this situation is the noticeable recent research production
on this subject in research conferences L. H. Crawford, 2010;
Kulvik, Poskela, Turkulainen, & Artto, 2010; Winch, Meunier, & Head, 2010)
and in specialized project management journals (Aubry, Hobbs, Müller, &
Blomquist, 2010; Hurt & Thomas, 2009; Pellegrinelli & Garagna, 2009). This
statement can also be extended to other project management subjects that
pertain to the organizational level (as opposed to the project level) such as
program, portfolio, business projects, and so forth.
One interpretation of the vigor of this research trend suggests that
research has not yet delivered those answers needed to help professionals
solve their problems. In a more critical approach, it can also be interpreted
as a fashion nurtured by, among others, researchers themselves. To avoid the
fashion effect and the fade out, L. H. Crawford (2010) suggested going back
to what PMOs really do and focus on their functions. In parallel, project
management structures continue to evolve. When considering a PMO as an
organizational innovation, Hobbs and colleagues (Hobbs, Aubry, & Thuillier,
2008) showed that the PMO is still in a ferment era. The phenomenon is not
stabilized yet.
Until recently, empirical research has primarily looked at individual
PMOs, often because organizations had only implemented a single PMO to
serve project management needs. Some of the well-researched questions
related to PMO models (Hobbs & Aubry, 2010), performance (Dai & Wells,
2004), or frequent transformations (Aubry et al., 2010; Hurt & Thomas, 2009).
With some exceptions, however, there is only limited quantitative validation
to concepts and propositions regarding PMO performance (Dai & Wells,
2004), PMO typologies (Hobbs & Aubry, 2008), or patterns of change (Aubry
et al., 2010).
More recently, large organizations have started to implement multiple
concurrent PMOs, each one having different mandates, functions, and characteristics.
From previous workshops in which the authors have participated,
they know that implementation of multiple PMOs is often not coordinated;
this results in multiple PMOs working in isolation, which is rather surprising
given that project-oriented organizations were developed to break
these silos of functional units (Burns & Stalker, 1961; Turner &
Keegan, 1999). Organizations are now searching for a better articulation
among their PMOs and within their overall governance structure. As of now,
A Relational Typology of Project
Management Offices
Ralf Müller, Department of Leadership and Organizational Behaviour, BI Norwegian Business
School, Oslo, Norway
Johannes Glückler, University of Heidelberg, Heidelberg, Germany
Monique Aubry, School of Business and Management, Department of Business and
Technology, Université du Québec a` Montreal, Québec, Write my essay for me – CA Essay writer Canada
ABSTRACT ■
This explorative article develops a relational
typology of PMOs based on their roles with
stakeholders. A multi-case study was used to
identify the roles of PMOs in multiple-PMO settings.
A three-dimensional role space allows
locating the complex relational profiles that
PMOs take on with respect to their stakeholders
in practice. Superordinate, subordinate, and
coequal roles were identified in a framework of
servicing, controlling, and partnering in organizations.
While servicing (subordinate role profile)
and controlling (superordinate role profile) support
organizational effectiveness and exploitation
of knowledge, partnering (coequal role profile)
creates the slack necessary for potential exploration
of new knowledge.
KEYWORDS: PMO; PMO networks; relational
typology; organizational slack; innovation;
learning
Project Management Journal, Vol. 44, No. 1, 59–76
© 2013 by the Project Management Institute
Published online in Wiley Online Library
(wileyonlinelibrary.com). DOI: 10.1002/pmj.21321
60 February 2013 ■ Project Management Journal ■ DOI: 10.1002/pmj
A Relational Typology of Project Management Offices
PAPERS
the authors are not aware of any academic
research that has looked at this
multi-PMO phenomenon.
Instead of looking at one PMO at a
time, this article suggests considering
multiple PMOs within an organization
and understanding the consequences
of the diverse PMO roles for organizational
outcomes. For that, the authors
raise the following research question:
What is the nature of PMO in terms of relationships
within multi-PMO organizations?
Our unit of analysis is the
relationship between a PMO and its
stakeholders, and among other project
managers, peer PMOs, and/or some
project-related governance entities within
the organization.
Complementary to prior conceptions
and typologies of PMO characteristics
(e.g., Hobbs & Aubry, 2008), this
approach does not only qualify PMOs
by their internal conditions and characteristics
but, in addition, focuses on the
relations that PMOs establish with their
stakeholders. The value of such a relational
perspective on PMOs, we argue, is
that the actual relations between PMOs
and project managers will have a strong
impact on the way an organization
learns. It is assumed that innovations in
project management depend on effective
knowledge sharing between experts
in an organization. Specifically, the
authors hypothesize that PMO roles
affect the quality of knowledge exchange
and thereby leverage innovation. This
article pursues two concrete objectives:
First, it seeks to understand fundamental
types of PMOs from a role perspective,
both conceptually and empirically.
Second, it explores the impact of different
PMO role models on organizational
learning and innovation in the field of
project management.
The article is structured as follows.
The section on Conceptual Framework
develops the PMO role typology by distinguishing
three ideal role types that
PMOs can establish with their stakeholders
and the impact those PMO
roles may have on performance in
terms of slack and innovativeness. By
combining the literature of organizational
learning and the role triangle, we
develop propositions about the effects
of particular PMO roles on innovation
in project management. The section on
Methodology reports the research
design and methodology of a multiple
case study approach, data collection,
and analysis. The next section, Case
Study Descriptions and Findings,
reconstructs four organizational case
studies by analyzing the PMO roles. The
section on Effects of PMO Roles interprets
the cross-case findings by use of a
graphical representation, the role triangle.
The Homework help – Discussion section brings four
themes into the discussion, and the
article closes with the conclusion.
Conceptual Framework
Role Typology Based Upon PMO
Relationships
PMOs are extremely heterogeneous—
they vary in size, mandate, functions,
and so forth—and they are very
ephemeral in nature. One of the few
extended surveys on PMOs found that
the majority of PMOs observed had
been implemented within the last 24
months only (Hobbs & Aubry, 2010).
Given the seeming volatility and contextuality,
there have been quite a
number of efforts to detect underlying
commonalities and generalize concrete
ideal types of PMOs (Hobbs & Aubry,
2008); however, most of these typologies
focus on characteristics or attributes of
PMOs. This article takes a different
typological approach. First, it focuses
on the relationships that a PMO establishes
with its intra-organizational
environment rather than its internal
characteristics. Second, the typology
aims at identifying real types rather
than ideal types in order to support
management practice.
Given the focus of this article on relationships,
we adopt a perspective of
roles. A role describes a set of mutual
expectations between two actors about
their pattern of behavior and interaction.
A role perspective is helpful to understand
relational social and organizational
structures in that it focuses on the
kinds of interactions and interdependencies
between organizations or organizational
units. In the context of project
management, the role concept has been
applied to the division of labor between
project work and the project–client interface.
Turner and Keegan (2001) observed
that projects typically require two areas
of management: internal project management
and the management of the
external needs and claims by the client.
They consequently distinguish the roles
of the steward and the broker. This confirms
role differentiation within project
management dealing with different
stakeholders (Turner & Keegan, 2001).
Instead of focusing on projects, the
focus of this article is on PMOs and
the potential roles that they take vis-àvis
their stakeholders. A closer look at
one of the most established definitions
of a PMO serves as a starting point:
“[A PMO is] an organizational body or
entity assigned various responsibilities
related to the centralized and coordinated
management of those projects
under its domain. The responsibilities
of the PMO can range from providing
project management support functions
to actually being responsible for the
direct management of a project”
(Project Management Institute [PMI],
2008, p. 443). This definition has two
important implications: first, the concept
of the PMO covers a wide range of
organizational designs, competencies,
and interdependencies with the rest of
an organization; second, the authority
of a PMO may range from mere “support
functions” to the actual responsibility
“for the direct management of a
project.” This article contends that this
makes a difference for the nature of
relationships and for the organizational
outcomes, whether a PMO operates as
a service unit or a management unit.
The central argument of this article
is that PMOs relate in different (a)symmetric
ways with their stakeholders.
February 2013 ■ Project Management Journal ■ DOI: 10.1002/pmj 61
Three roles have been identified: serving,
controlling, and partnering. Some
PMOs, for example, are pure service
units, others are management units
that directly control projects and evaluate
the performance of projects or even
staff, and again others cooperate on continuous
improvement of project knowledge
by means of reciprocal knowledge
sharing with their stakeholders. The
central difference between these three
pure roles is the (a)symmetry in their
relationships: management authority is
a dominating role, service support
responds to demand and is a complementary
or even dependent role, and
cooperation reflects a collegial role
of partnership. Definitions of the
three PMO roles are provided in the following:
• Serving. PMOs exert a serving role if
they operate as a service unit to internal
and external units, project managers,
and project workers. Typically, a
PMO offers a number of support functions
to projects in order to increase
resource efficiency and outcome
effectiveness. In a serving role, a PMO
extends the administrative capacity of
a project and provides for operational
support in projects through training,
consulting, and specialized task execution.
It responds to stakeholder
needs and ensures overall project performance.
• Controlling. At the other end of the
asymmetry, PMOs take a controlling
role when they operate as management
units for projects under their
domain. Depending on the scope of
managerial authority for which they
are commissioned, PMOs may be
responsible for the enforcement of
project management standards such
as methods and tools, for the control
of compliance with set standards, for
evaluation of project performance,
and sometimes even for the assessment
of employee performance and
career promotion. Whenever PMOs
are entitled not only to monitor and
evaluate but also to take managerial
action and sanction malpractice, they
exert a role of relative dominance and
surveillance over project managers
and project workers.
• Partnering. A third role, not particularly
acknowledged in PMO research
is the partnering role. The partnering
dimension has received limited or no
attention so far and is not explicitly
acknowledged in the seminal PMI definition
(PMI, 2008). Partnering refers
to a relationship that is characterized
by reciprocity, mutuality, and equality.
Partnering implies lateral communication
between a PMO and other—equally
qualified or equally commissioned—
PMOs, project managers, or project
workers. Such a coequal relationship
would enable or emerge from cooperation
and mutual interdependencies.
More concretely, a PMO takes on a
partnering role when it engages in
equal knowledge sharing, exchange of
expertise, lateral advice giving, and
joint learning with equal level stakeholders.
PMO Role Profiles, Organizational
Slack, and Performance
The role typology developed in the previous
section is not an end in itself but
is proposed as a strategic tool to assess
the potential contribution of a PMO to
diverse organizational outcomes. Once
a PMO role profile is classified and
mapped in the ternary role model,
questions arise about the effects of this
role profile on corporate performance.
As of now, academic research is unable
to statistically relate PMO characteristics
and functions to its performance
expressed in terms of financial indicators
(Kwak & Ibbs, 2000) or project performance
(Dai & Wells, 2004). One more
promising approach would be to
extend the concept of performance
to include a diversity of perspectives
such as those suggested within the
competing values framework (Quinn &
Rohrbaugh, 1983). This framework is
based upon the assumption that organizations
are diverse and that multiple
and competing values coexist. It
already has been shown that the PMO
contribution to the organizational performance
can be captured using this
framework (Aubry & Hobbs, 2011).
Efficiency and other financial ratios are
parts of the competing values framework
but also include criteria from
human relations, innovation, and internal
processes. Such a perspective of
multiple performance criteria, however,
stands in contrast to the evolution of
the common approach to project management.
Projects are organizational
tools used to optimize resource input to
achieve a certain goal in time, cost, and
quality. Although projects are a means
to accomplishing short-termed tasks
effectively and efficiently, they are not
designed for long-term innovation. To
prioritize short-term achievements
over long-term improvement is one of
the critical learning myopias identified
by Levinthal and March (1993).
Therefore, this article takes a closer
look at the conditions that fundamentally
enhance learning, knowledge
transfer, and innovativeness of a PMO
and project management. PMOs are a
novel intra-organizational form to
support project management and to
leverage performance and sometimes
innovation in project management.
However, knowledge is often very sticky
(Szulanski, 2003), its transfer is difficult
to achieve, and it imposes high costs of
making new practice available and
usable to other parts of an organization.
As Porter (1985) witnesses from
decades of research in corporations,
“the mere hope that one business unit
might learn something useful from
another is frequently a hope not realized”
(p. 352). Under what conditions
do organizations innovate? Ever since
March’s seminal work, one fundamental
rule has become visible: rational
organizations tend to prioritize the
commercial exploitation of existing knowledge
over the exploration of new
knowledge, because exploitation yields
immediate profits, whereas exploration
62 February 2013 ■ Project Management Journal ■ DOI: 10.1002/pmj
A Relational Typology of Project Management Offices
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(i.e., research, development, and learning)
are investments into future profits
with higher levels of uncertainty
(March, 1991). Learning processes are
subject to myopia because organizations
tend to overlook distant times,
distant places, and failures (Levinthal &
March, 1993).
One approach to maintain exploration
and experimentation despite the
incentives to focus on short-term
exploitation is organizational slack.
Theoretically, the basic assumption is
that every firm purchases and uses all
of its inputs efficiently; however, “the
data suggest that there is a great deal of
possible variation in output for similar
amounts of capital and labor and for
similar techniques, in the broad sense,
to the extent that technique is determined
by similar types of equipment”
(Szulanski, 2003, p. 404). This x-efficiency
is defined as the discrepancy
between actual output and maximum
output for a given set of inputs
(Leibenstein, 1966).
In its classic definition, slack refers
to the “disparity between the resources
available to the organization and
the payments required to maintain the
coalition” (Cyert & March, 1963, p. 36).
Examples of slack are excess dividends
to shareholders, higher wages than
those needed to keep labor, or the supply
of uncommitted resources. Slack is
the “cushion of actual or potential
resources, which allows an organization
to adapt successfully to internal
pressures for adjustment or to external
pressures for change in policy, as well
as to initiate changes in strategy with
respect to the external environment”
(Bourgeois, 1981, p. 30). Cyert and
March (1963) hypothesize a positive
effect of slack on performance; however,
slack does not produce endless
advantage. Empirical studies in multinational
firms suggest that organizational
slack enhances experimentation
but that it also reduces discipline over
innovative projects, resulting in a
U-shaped relationship between slack
and innovation (Nohria & Gulati, 1996).
Projects are by definition opposed
to slack and experimentation because
their primary task is to complete objectives
in time, cost, and quality. Projects
usually are the device of efficiency. The
concept of organizational slack has
merely been applied to innovation in
project management. One interesting
exception is an explorative case study
by Keegan and Turner (2002) that found
an accordion effect in which slack
resources were tolerated more in some
situations than in others: “According to
descriptions of respondents, it seems
that following a period of poor innovative
outcomes, slack resources are considered
as potentially important for
innovation and more resources are subsequently
made available. On the other
hand, when positive results are slow to
emerge, the mood changes, and slack is
seen as negative and inefficient use of
resources” (p. 377). Consequently, the
authors conclude that for projects to
perform good innovation projects, new
management techniques are necessary
to respect slack resources and use overcapacity
to leverage real innovation.
What is slack in the context of PMOs
and how could PMOs be fitted to
enhance innovation in project management?
We see at least three areas of
missing slack in PMO organizations: (1)
short life span; (2) missing human
resources dedicated to knowledge sharing
and innovation; and therefore (3), a
limited engagement in a partnering role
with other stakeholders. First, according
to prior extensive research, PMOs
tend to live short time spans (Hobbs &
Aubry, 2010). Although the potential
benefit of short-lived PMOs points
toward their adaptability to changing
situations of project management in an
organization, it also implies a dangerous
weakness. The fact that PMOs are
implemented to meet certain objectives
and that they are dissolved immediately
after accomplishment reflects
organizational efficiency. However, it
also reflects a lack of slack in organizational
capacity to consolidate lessons
learned, to follow-up on achievements
and critical experiences and to develop
new knowledge about project management
perspectives, methods, or concrete
techniques. This is in line with
results from Williams (2007), confirming
the difficulty to document lessons
learned from projects.
Second, PMOs are often quite small
units with limited human resources.
PMOs are designed for efficient
resource use and effective project management
outcomes—time, quality, and
cost targets. Hence, PMOs are often
underequipped with personnel that
takes care of collecting experience,
sensing “better” practice, and developing
new templates for innovative practices
in project management. Third,
and consequently, we expect that the
efficiency focus will lead to a predominance
of serving or controlling role profiles
in which PMOs either offer support
to efficient project management or take
the management responsibility directly.
Instead, partnering role profiles as
suggested in the PMO role triangle
would create slack through mutual
knowledge exchange, reflective action,
and feedback loops rather than purely
leveraging efficient project execution.
This article hypothesizes that PMO
partnering creates slack and supports
creative processes in yielding original
project management innovation (see
Figure 1).
Methodology
This study uses an abductive epistemological
approach within a critical realist
perspective (Archer, Bhaskar, Collier,
Lawson, & Norrie, 1998; Sayer, 2000).
Because the research question focuses
on a new understanding of the nature
of PMO relationships, the corresponding
research strategy follows a qualitative
methodology. The reality of a single
PMO is quite well known; however, little
is actually known when considering
multiple PMOs and their relationships.
In this context, the first research step to
be undertaken is the understanding of
the phenomenon within its context
(Patton, 2002). This goal is better
February 2013 ■ Project Management Journal ■ DOI: 10.1002/pmj 63
reached within a qualitative approach
such as case studies (Eisenhardt &
Graebner, 2007). We adopted a multiplecase
design, which implies replication
logic (Yin, 2009) within which a case is
treated as an idiosyncratic expression
of the phenomenon under study. Four
organizations have contributed to this
research. Data were mainly collected
through semi-structured interviews.
Other complementary data were
obtained from interviewees (such as
internal reports, presentations, and so
forth) or from public information on
company websites. Organizations were
selected to offer a strong research
design with a mix between homogeneity
and heterogeneity (Eisenhardt,
1989). All four organizations share
some characteristics: they are large and
they have formalized their project management
processes through implementation
of more than one PMO. On the
other hand, each organization is specific
to its geographical region and economic
sector. In each organization, interviews
were realized with individuals representing
a variety of roles, such as PMO
director, its supervisor, and project manager.
A total of 46 semi-structured interviews
were conducted. (See Table 1 for
the details on organizations and interviews.)
In line with Yin (2009), validity
was assured by looking for multiple
sources of evidence and by having the
key-informants reviewing the research
report and findings. Reliability was
assured through replication logic.
Interview data were analyzed by
using different and complementary
strategies (Langley, 1999). The interviews
followed a grounded theory approach for
each individual case. In line with an
abductive approach described for the
cross-case analysis, the grounded theory
approach followed the Glaser and
Strauss (1967) school. This implies an
analysis after each individual interview
and a continuous comparison approach
to identify commonalities, as well as
ruling out one-time events, thus ensuring
a robust theory. Interviews in the first
case study were registered, transcribed,
and then analyzed using ATLAS.ti
(ATLAS.ti Software Development, 2004).
In the three other case studies, interviews
were recorded and notes were taken by
the researcher during the interview and
were promptly analyzed; then, following
Miles and Huberman (1994) and
Eisenhardt (1989), we undertook crosscase
analyses to develop the underlying
concepts. There was a steady back and
forth between data from the cases and the
identified concepts in order to ensure that
the concepts were consistent with the
data (and valid). Within each case, multiple
respondents participated in semistructured
interviews to provide reliability
of results. For each PMO, data were crossvalidated
between respondents.
Case Study Descriptions and
Findings
In this section, the four case studies are
first shortly described in their specific
contexts; then, the structure of the
PMO’s network is described and analyzed
under the three basic PMO roles
(serving, controlling, and partnering).
For each case study, a synoptic table
summarizes findings and presents the
intensity of roles for each PMO.
Case 1:Healthcare Service Provider
Context
This case study is a public healthcare
service provider constituted of quasiautonomous
organizations spread over
three structural layers: national, regional,
and local (hereafter, Healthcare).
Like in many western countries, the
healthcare system is facing major challenges,
such as the aging population,
lack of personnel, outdated facilities,
sub-optimal processes, and so forth.
Major investments are therefore authorized
and aimed at the healthcare
system’s renewal. Projects include construction
of new hospitals, clinical
processes reengineering, and implementation
of new technologies. Stakeholders
and change management are crucial to
success. Project management practices
PMOs ROLES IN THEIR
RELATIONSHIPS
PERFORMANCE
• Serving
• Controlling
• Partnering
• Slack and
innovativeness
• Ambidexderity
Figure 1: Conceptual model: Relations between PMO roles and performance.
Case #1 Case #2 Case #3 Case #4 Total
Geographical location North America Europe Asia Europe 4
Economic sector Healthcare Telecommunication Pharmaceutical Finance 4
Number of PMOs investigated 11 7 5 4 27
Number of interviews 21 7 10 8 46
Table 1: Case study descriptions.
64 February 2013 ■ Project Management Journal ■ DOI: 10.1002/pmj
A Relational Typology of Project Management Offices
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are quite well established at the national
level but are often limited to the IT
sector. There are various roles to PMOs,
depending on their level and on their
leadership to implement and develop
project management competencies. Project
methodology has been adopted since
being at the national level for a few
years and is actually in implementation
at the other levels. Since 2004, rigorous
governance rules have been applied to
project management.
Structure of the PMO’s network at
the healthcare case study mirrors the
organizational three-layer structure:
national, regional, and local levels. At
the national level, there are three
PMOs. One PMO is located within the
IT department. This national IT PMO is
primarily responsible for project portfolio
management and more specifically
concerned with investment strategy,
project coordination, project
control, and so forth. It also aims
at enhancing the overall project management
competencies by the implementation
of project management
methodology, tools, and techniques at
the regional level. Projects are realized
by a private partner, outside the national
IT PMO. This PMO also manages a
PMO coordination committee where all
regional PMO directors meet on a
monthly basis. This committee serves
as a sharing and learning mechanism,
resulting in spreading out best practices
to enhance the project management
competencies. The second PMO
at the national level is dedicated to the
specific project of Personal Health
Record (PHR). The third one is the
delivery arm to the national IT PMO
where projects are realized.
The 18 regional PMOs have been
put in place following a recommendation
from the national level. The majority of
them are located in the IT department
even if projects are rarely purely IT. There
are large variations between these 18
PMOs regarding their size and their
maturity in project management, and
these PMOs are accountable for the
implementation of the projects in local
settings. Their project managers are
particularly interested in the implantation
strategy and change management.
Multiple informal links exist
between regional PMO directors
and between regional and local PMO
directors. There is a climate of collaboration
and help.
Local PMOs are located in a global
local center and within individual hospitals
and healthcare centers. This level
also includes university hospitals;
therefore, they are in direct contact with
patients. There are approximately 100
PMOs disseminated over these local
healthcare institutions. Some variations
in size and project management maturity
exist between the local PMOs. The
biggest PMOs are actually found in university
hospitals, because major investments
are placed there. PMOs are often
specialized in construction, IT, or
process reengineering. Project managers
often have certified qualifications.
Identifying PMO Roles
Eleven healthcare PMOs participated in
this research. The analysis of their relationship
under the basic PMO roles
permits identifying five different groups
of PMOs that are presented in more
detail in the following paragraphs (see
Table 2).
1. PMOs at the national level (national
IT PMO and PMO for PHR project).
These PMOs perform two high-level
functions for controlling and partnering
in relationship with other
PMOs. On one hand, they strongly
control projects within strict governance
mechanisms. The national IT
PMO asks the local hospital PMO to
report periodically on their projects’
costs expenditures and projections
and asks for financial indicators or
for more global value-added indicators.
On the other hand, the same
national IT PMO initiated a knowledge
platform for use by all PMO
managers and project managers. This
effort could be regarded as a communities
of practices activity. It takes the
form of a national committee, one
grouping regional PMO directors and
the other grouping regional project
managers. The ultimate goal is to
develop and engage the national
healthcare system in project management.
In the short term, the
objective is to share good practices
and to develop together any missing
processes or tools. The partnering
shows less intensive function in the
implementation of project portfolio
management. Actually, there is no
inventory of all projects going on at
all three levels in the healthcare
national system, and consequently,
there is no idea of the global
resources allocated to projects.
However, regional and local organizations
sometimes perceive this initiative
as an intrusive approach. The
serving function is performed at a
very low level.
2. National IT supplier and local PMOs.
These PMOs concentrate their most
important function on the controlling
and do not perform that much of
the partnering and serving. This
function is accompanied by strong
project management techniques and
strict methodology, processes, and
tools. The national IT supplier PMO
adopted a strategy of suppliers to
deliver IT software components. This
PMO manages a portfolio of contracts.
With strong project management
methodology, processes, and
tools, this PMO can monitor and
control its suppliers’ work. Not surprisingly,
this PMO owns an ISO certification
in project management.
Local PMOs dedicated to IT or real
estate projects could also be associated
with this national supplier PMO.
3. Regional PMOs. These PMOs present
a strong function of serving clients.
Everything is turned toward this goal
of satisfying the needs of their clients.
Their mandate covers two types of
projects based on their clients: internal
client—more often from a functional
unit—and local needs where clinical
solutions are directly implanted for
PMO BASIC ROLES
PMO Identification Serving Controlling Partnering
1. National IT PMO and PHR PMO LOW HIGH HIGH
• Serving functions are less present at the national • Monitor and control projects costs/ • Knowledge of national platform
level schedule/content particularly with local with regional PMO directors and
PMO for major projects and with the project managers
national IT supplier PMO
MODERATE
• Implementation of project portfolio
management: inventory of
projects
2. National IT supplier and LOW HIGH LOW
Local PMOs • Develop methodology, processes,
and tools
• Monitor and control projects costs/
schedule/content particularly with major
projects sub-contractors
3. Regional PMOs HIGH LOW TO MODERATE MODERATE
• Develop and implement methodology, • Monitoring and control of projects under • Participation to the national
provide tools their mandate PMO coordination committee
• Manage projects under their regional mandate • To local PMO directors: informal
• Provide support to project teams for project not sharing of good practices
directly in their mandate Low partnering function:
• To internal organizational governance:
not that much included
4. Regional/Local PMO HIGH LOW HIGH
• Develop a project management framework, • PCO: not acting as controller but collect • Participation to the national
including methodology, processes, and tools information to present a global view of PMO coordination committee
• Manage project in a coaching approach the project portfolio. Soft approach • With regional and PMO
• Provide support to project teams for project not management language directors: informal sharing of
directly in their mandate good practices
• Participate and influence internal
organizational governance
5. University hospital MODERATE MODERATE MODERATE
• Clear mandate to support organizational change • To national project governance: provide • Executive Board members as
• Manage projects: Co-construction with project team strict monitoring and control of “partners” to the PMO
• Innovation is encouraged project. A specific function of the PMO • Knowledge acquisition and
• Support project management within a is to evaluate projects and project transfer through projects
multidisciplinary advisor committee management financial report. • Strong relationship with other
functional departments
Table 2: PMO roles in Healthcare case study.
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patients. They manage the project for
the former and the support projects
for the latter. Following this serving
approach, control of the project is
rather low. Considering now the partnering
function, PMOs of this type
are at a low or moderate level. They
are at a low partnering level when
considering its role vis-à-vis the
internal organizational governance.
This type of PMO is only partially
involved in governance. But, when
taking specifically a project management
perspective, this PMO participates
in partnership at the national
level as a member of the PMO’s coordination
table. These PMOs are also
associated with other local or regional
PMO directors for sharing experience
in an informal approach.
4. Regional/local PMO. This PMO has a
particular double mandate, including
regional and local responsibilities.
Like regional PMOs, it has a
strong serving function dedicated to
internal clients and to local needs
and quite low control over projects.
This PMO has developed its own project
management framework, which
includes methodology, processes,
and tools. It has a soft approach to
their clients in order to get them
engaged softly in project management;
however, this PMO has a
strong partnering function. Its director
participates very strongly in the
national PMO’s coordination committee
and in other specific working
subcommittees. He also created
other networks between PMO directors
to share and build new components
within the project management
framework. This PMO participates
actively in the internal organizational
governance. The project management
framework is at a point of being
accepted at the organization level
as a common project management
language.
5. University hospital PMO. This PMO
might be quite exceptional, showing
moderate results in all three dimensions
of serving, controlling, and
partnering. It refers to a PMO in a
university hospital with a mandate to
accompany a major organizational
change. Serving clients is clearly in its
mandate. Generic project methodology
processes and tools have been
developed but are adapted to each
specific project’s needs. Innovation
in management is encouraged. A
multidisciplinary advisory committee
has been put in place for the PMO
to support the entire organization in
project management and, ultimately,
in managing changes. This PMO has
also provided results to the national
governance level within strict financial
limitations. A specific function
within the PMO is to evaluate projects
and project management financial
performance and to report on it.
Turning now to partnering, this PMO
establishes strong internal links; it
participates in the executive board,
where members are considered as
partners of the PMO (PMOs have
given them the title of Partner).
Another partnering function relates
to knowledge management. This
PMO has implemented a specific
function to collect and share knowledge
through projects and a specific
role of knowledge broker. They want
projects to be based on evidencebased
data. This is true for clinical content,
but also for management
content. PMO has taken the leadership
to establish strong relationships
with other functional departments,
such as human resources or quality
management. Common project
management processes were developed
to insure a common and appropriate
contribution from those units
to projects.
Case 2:Mobile Phone Development
and Manufacturing
Context
The company is a long established global
telecommunications company, headquartered
in Northern Europe, acting as
a main player in a fast moving and competitive
market (hereafter Telecom).
Project management is a well-established
role in the organization. Most of the
project managers are professionally certified,
formally assigned to projects, and
respected in this role. The projects are
telecom projects for systems integration,
multimedia, or network rollout.
Project performance is assessed in
terms of reaching targets for time, budgets,
quality, and customer satisfaction.
The particular role of the PMOs is to
provide subject matter expertise in project
management for particularly important
projects, and within countries
where the required expertise is not (yet)
built up locally. Dedicated methodologies
are in place for both project management
and project governance (see
Table 3).
Identifying PMO Roles
The PMO network consists of approximately
200 individual PMO organizations,
with approximately 500 members
altogether. The network is hierarchically
structured in a PMO at Headquarters,
as well as those at the global, regional,
and country levels.
1. Headquarters PMO. This PMO develops
and owns project management
in the corporation. The hierarchical
concept of the PMO network is developed
here and deployed through the
other PMOs. The main task is in policy
development and deployment,
which includes new tools, techniques,
training, and certification programs.
Feedback on the scope and depth of
deployment at the regional and country
levels is through the work of
the global PMO. Synchronization of the
different PMOs takes place through
common charters, objectives, and
incentives, as well as missions tailored
for the different layers of the
network hierarchy. The mission of
the Headquarters PMO is to establish
world-class PMOs and be recognized
in the market for this.
2. Global PMO. This PMO works as the
interface between the Headquarters
PMO and the regional PMO by serving
the Headquarters in terms of
February 2013 ■ Project Management Journal ■ DOI: 10.1002/pmj 67
managing global deployment but
also in assessing and evaluating project
management maturity in the
regions. The latter includes control of
regional PMOs. The majority of work is
done in partnership with the regional
PMO for tailoring Headquarters
deployment blueprints to the needs
of the regions, supporting regions in
balancing resources across organizational
and country borders, as well
as organizing global knowledge
exchange events. The global PMO
synchronizes with the regional
PMOs through key performance
indicators.
3. Regional level PMOs. Regional level
PMOs work mainly in partnering functions
on the recovery of troubled projects
or as “place holders” in case of a
lack of skills in a particular country
organization. In the former role, they
work with country-level project managers
on project recoveries and on
skills transfer. In the latter role, they
serve a country organization by managing
projects within a country until
local skills are deployed. Some control
through standardization and improvement
of project management within
the organization is also done here, but
only by a few PMO members.
4. Country level PMOs. The mission for
country and regional level PMOs is to
provide resources for balancing competencies
across borders. Country
level PMO members manage projects
at customer sites toward set objectives
in terms of time, cost, quality,
and customer satisfaction.
Case 3:Pharmaceutical Development
and Manufacturing Company
Context
This company is a relatively young
development and manufacturing
company of medical and healthcare
products with Headquarters in 论文帮助/论文写作服务/负担得起我及时提交我最好的质量 – China
(hereafter, Pharma). Since its start-up,
the company has grown extensively
within an established, but competitive
market. The majority of its 30,000 people
workforce is employed in 论文帮助/论文写作服务/负担得起我及时提交我最好的质量 – China; however,
cooperation with other institutions
and sales are done worldwide. Project
management is a well-established function,
with approximately 100 (in their
majority certified) project managers.
Projects are classified by scope and complexity
(A strategic, B cross departmental,
C within a line function).
Project managers are assigned to projects
based on their project management
experience (see Table 4).
Identifying PMO Roles
The PMO is a virtual organization within
the company’s headquarters. It consists
of the PMOs of different departments.
Each PMO representative at the
Headquarters level functions in a dual
role as department manager and as a
PMO in his or her respective organization.
At the Headquarters level they are
referred to as an expert group for project
management. This group consists of
six members plus a manager. These
managers frequently draw upon the
knowledge from an additional 12 project
management experts from within
the community of project managers.
The Headquarter PMO is supported
by a project information management
group for the communication in the
form of information collection and distribution,
mainly using an IT platform.
1. The Headquarter PMO. This PMO
selects projects; assigns project managers;
and provides the methods,
techniques, career path, certification,
and communication platform for
project managers. Simultaneously,
the PMO functions as the steering
committee and the escalation point
for projects in execution.
Development work within the PMO
(e.g., of new practices) is assigned to
PMO BASIC ROLES
PMO Identification Serving Controlling Partnering
1. Headquarter PMO LOW HIGH LOW
• Development and ownership of project
management, its processes, methods,
and policies
2. Global PMO LOW HIGH MODERATE
• Worldwide deployment • Tailoring to regional needs
• Evaluation of maturity
3. Regional PMO LOW MODERATE HIGH
• Manage projects on behalf of • Deployment of processes, methods, • Recovery of troubled projects
country project manager and policies • Knowledge transfer to local
project managers
• Tailoring to local needs
4. Country PMO HIGH LOW LOW
• Managing projects
Table 3: PMO roles in Telecom case study.
68 February 2013 ■ Project Management Journal ■ DOI: 10.1002/pmj
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a member of the PMO, who then
engages relevant experts. The final
product is reviewed by the PMO
expert group and may be adjusted
before deployment through the web
platform. Through this structure, the
PMO does not interfere with the project
managers’ day-to-day work but
governs project management in a
subtle but comprehensive manner.
Table 4 summarizes the roles and
functions of the PMO in this case.
Case 4:Financial Services Provider
Context
The organization is a leading co-operative
bank in Germany with approximately
7000 employees (hereafter, Financial).
A recent change of owner increased the
number of projects because of the need
to align the business and governance systems
of the two organizations. Project
and portfolio management are established
functions. Approximately 100
projects were ongoing at the time of
investigation. Four PMO organizations
exist within the bank some of them in a
hierarchical relationship, others at
a peer-to-peer level (see Table 5).
Identifying PMO Roles
The four PMO organizations are:
1. Business Project Office (BPO), reporting
to the executive board. This eightperson
PMO consists of a group for
portfolio management and an expert
group for finance, marketing, and
strategy projects. This is the “roof
organization” of all PMOs with a
holistic view over all projects. They
hold a strong controlling role
through ownership of the project
management process and by providing
portfolio management and
follow-up on projects; furthermore,
they ensure the communication
between business and IT functions.
2. Project Management and Strategic
Integration Office (PMSI),reporting to
the Executive Board. This 20-person
PMO focuses on IT projects and
serves as the interface between business
and IT. Their tasks include
translation of business into technical
PMO BASIC ROLES
PMO Identification Serving Controlling Partnering
1. Headquarter PMO LOW HIGH LOW
• Authorizing of projects • Knowledge transfer through training
• Ownership of processes, methods, and policies
• Project steering group
• Evaluation of project and project manager performance
• Certification program
Table 4: PMO roles in Pharma case study.
PMO BASIC ROLES
PMO Identification Serving Controlling Partnering
1. Business Office Project (BPO) LOW HIGH LOW
• Portfolio management of
country level projects
• Ownership of processes
• Project follow-up
2. Project Management and MODERATE LOW HIGH
Strategic Integration Office (PMSI) •Application testing • Interface business and IT
through translation of
requirements
3. Local IT PO HIGH LOW LOW
• Corporate-wide IT
projects
4. Strategic Project Office (SPO) MODERATE LOW MODERATE
• Project management • Definition of strategic projects
for some of the strategic
projects
Table 5: PMO roles in Financial case study.
February 2013 ■ Project Management Journal ■ DOI: 10.1002/pmj 69
requirements; assessment of impact
of changes on policies, structures,
and so forth; as well as testing of software.
In this role, they show a highpartnering
profile across the IT and
business functions of the organization.
Some minor serving is done by
testing software, which is developed
elsewhere in the organization in
accordance with specifications that
this PMO helped to translate from
business to IT language.
3. Local IT Project Office (Local IT PO),
reporting to the IT Operations
Committee, led by the chief information
officer of the new owner of the
bank (that is, another European
financial institution). This six-person
PMO manages, coordinates, and
tracks the largest IT change projects.
They focus on cross-organizational
IT projects, by doing this, they mainly
perform a serving function for and
within corporate-wide IT projects.
4. Strategic Project Office (SPO), reporting
to the Operations & Technology
(O&P) department. Their focus is on
strategic projects in O&P, which can
also be non-IT projects. This PMO
develops the strategies for the O&P
department. This constitutes a controlling
role; however, they also
define and manage some of these
projects. This constitutes a serving
role, so their combined role is the
most balanced role among all PMOs,
given by the balance of a partnering
and serving role in their work.
Central control lies with BPO, which
provides the interface structure of the
PMOs; however, PMO members feel
responsible to act informally across
organizations. This is especially visible in
the participatory decisions and synchronization
meetings, which have no central
manager, only a facilitator without an
ascribed position or responsibility.
The four case studies described and
analyzed previously provide a novel
approach to a PMO typology based upon
their relationship with stakeholders.
Results reveal differentiation between
PMOs within the three basic roles leading
to a specific location within one of the
four regions within a role triangle,
which constitutes the relational typology.
As said earlier, the typology is not an
end per se. It allows associating a PMO
type with capabilities, here learning
capabilities and support to innovation.
The following section highlights some
facets from these findings.
Effects of PMO Roles
Introducing the Triangle
The conceptual framework presented
in Figure 1 includes components that
capture relationships between PMOs
based on three base roles: serving, controlling,
and partnering. The four case
studies described above were analyzed
with respect to these roles. We argue
that potential responsibilities and
actions that PMOs take on can be
mapped into one of these three base
roles. In practice, however, each PMO
will most likely take on various roles
simultaneously and will thus exhibit a
complex profile made up of a mixture of
these roles. In order to capture such an
empirical role profile, we developed a
ternary role model that offers a location
for every theoretical combination of the
three base roles: serving, controlling,
and partnering. This typological
approach is best realized by use of a ternary
diagram.
A ternary diagram is a triangle that
displays the relative proportions of
three possible categories of individual
elements, which make up an aggregate
population. These categories must be
mutually exclusive and collectively
exhaustive (Plewe & Bagchi-Sen, 2001).
A labor market, for example, is composed
of employment, which is either
primary (agriculture), secondary (manufacturing),
or tertiary (services)
(Preusser, 1976). Ternary diagrams are a
graphical technique, which is common
in various disciplines (e.g., demography,
geography, chemistry, or pedology).
They are used to represent trivariate
data in which the three variables represent
proportions of a whole (Graham &
Midgley, 2000), such as the composition
of a territorially bounded population by
age (adolescent, adult, retired) or ethnicity
(Plewe & Bagchi-Sen, 2001), or
the composition of a population of
schoolchildren according to public, private,
or post-secondary schools
(Patterson et al., 2007). In the context of
PMOs, serving, controlling, and partnering
are clearly exclusive role elements
that combine into an aggregate
role profile. Within a three-dimensional
role space, each theoretical mix of roles
can be plotted as a specific role profile.
For reasons of simplicity, we distinguish
four role regions based upon role
profiles (see Figure 2): the superordinate
role profile (controlling), the subordinate
role profile (servicing), the
coequal role profile (partnering), and a
balanced profile in the center without
a focused orientation. Every PMO role
profile can now be located in this
role space. Within this conceptual
framework of a ternary role space any
concrete combination of roles that a
PMO exerts can be associated with a
particular role region and thus be located
as a ternary role profile. The diagram
can be used for different scales of
analysis, that is, at the level of the PMO
(mapping the distinct activities), at the
level of the organization (mapping the
different PMOs), or at the level of a
group of organizations (mapping the
distinct PMO cultures for a set of organizations).
PMO Role Profile
The case studies presented above can
now be analyzed using the role triangle.
In this section, a cross-case analysis is
presented comparing the four individual
case studies. As illustrated in Figure 3,
PMO networks can be drawn for each of
the case studies showing interesting
results about PMO relationships.
Except for the Pharma case, the
other three case studies show a variety
of PMO roles. PMOs at the top apex in
the superordinate profile are positioned
higher in the organizational
hierarchy. They share the accountability
for project results with respect to scope,
70 February 2013 ■ Project Management Journal ■ DOI: 10.1002/pmj
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budget, and schedule. This is obvious in
Telecom and Finance, where PMOs at
the top level have direct formal authority
over PMOs at the regional level. In
Healthcare, the two superordinate
PMOs are not in a position of formal
authority over the other ones, but they
have established relationships under
the control of projects. In Pharma, the
virtual PMO has clear authority over
project managers, for example, through
the annual assessment. Altogether, the
position of PMOs within the triangle
and the analysis of their position within
the organizational chart may be contrasted
to the hierarchical PMO model
suggested in K. J. Crawford (2010),
where multiple PMOs coexist at different
hierarchical levels without taking into
account their relationships. However,
to date, no research has identified a
clear correlation between organizational
hierarchy level and the function
of a PMO, for example, monitoring and
control of projects (Hobbs & Aubry,
2008).
Results also show PMOs in serving
roles. In three cases, these PMOs are
directly managing projects; they are in
between a PMO that asks for control
and other PMOs that are implementing
projects.
On the partnering apex, there are
three PMOs offering different interpretations.
In Telecom, this regional level
PMO has clearly in its mandate to support
and help in troubled projects. This
function has more chance to succeed in
a partnership type of relationship,
where learning is a value rather than a
fault culture often associated with control.
In Healthcare, this PMO maintains
rich network opportunities through
implication of its director at different
organizational levels. Under this PMO
leadership, many new project management
initiatives have been implemented
on a voluntary basis and diffused
throughout the whole network. In
Finance, the coequal PMO type has a
strategic mandate with a translation
responsibility between business and IT.
In this particular case, partnership
appears to be a good approach to opening
up a dialogue between stakeholders
that more often have different perspectives
on projects.
At the central part of the triangle,
the balanced PMO role is positioned,
reflecting equilibrium in the intensity
of controlling, serving, and partnering.
Two PMOs are at this triangle position.
In the Healthcare case, the PMO has a
controlling relationship over the projects
it manages because it has great
pressure from upper levels to respect
the budget and make projects contribute
to the ROI. On the other hand,
in the healthcare sector in general, the
project management standardization is
rather low. The approach this PMO has
developed with PMOs in clinical projects
is to serve and help participants
grow their projects and learn constructively.
This PMO has also developed
partnerships with other functional
units, which otherwise would have possibly
entered in tensions or power
struggles (Aubry, Hobbs, Müller, &
Blomquist, 2011). In short, this PMO in
Healthcare undertook strong actions in
all three roles. In Finance, the PMO
undertook rather moderately strong
actions in each role.
Slack and Innovativeness Through
Partnering Roles
In this section, a cross-case analysis is
presented taking an integrative view of
the 27 PMOs identified in this research.
Figure 4 suggests a new interpretation
from the qualitative case studies.
Interestingly, what could be
observed from Figure 4 is that the distribution
of PMOs in the ternary diagram
Serving – +
Controlling – +
– Partnering +
Subordinate
PMO role
Coequal
PMO role
Balanced
PMO role
Superordinate
PMO role
Figure 2:The PMO role triangle.
February 2013 ■ Project Management Journal ■ DOI: 10.1002/pmj 71
shows that PMOs are more likely to take
on controlling or serving roles rather
than partnering roles, with both being
separated by a bold line with nine out of
fourteen PMOs. Some of the circles
stand for more than one individual
PMO. When taking the reference to the
number of individual PMOs, it is 10 in
the controlling role and five in the serving
role out of 21 PMOs, or globally, 71%
for both roles. The five other PMOs are
associated with the partnering role.
Controlling is the most common
role and can be associated more specifically
with the PMO function of monitoring
and controlling projects. This
result is in line with previous research
that has shown that this function is the
most important one and one that is
under the mandate of most PMOs
(Hobbs & Aubry, 2010). Conversely, the
serving role is associated with a collaborative
approach to internal clients. In
this role, a PMO is more likely to offer
services to project management stakeholders.
The serving PMO will negotiate its
own mandate to answer the specific
needs of stakeholders and to respect
the relationship with it (Huemann,
2010). Instead of imposing a methodology,
a process, or a tool, this approach
supposes that the PMO will adapt its
solution to the need and the degree of
formalization of each stakeholder.
These PMOs share a certain degree of
fear of being rejected; being rejected
may mean attacking the PMO’s legitimacy.
Fifty percent of PMOs have been
put into question over their last two
years (Hobbs & Aubry, 2010). Avoiding
conflict to maintain PMO survival was
the strategy of some of PMOs in the
serving role.
Developing partnerships with
stakeholders takes time and engagement
for long-term relationships. It
may seem curious to invest resources in
a long-term partnership knowing that
projects are temporary organizations
(Lundin & Söderholm, 1995; Turner
Serving – +
Controlling – +
Partnering
TELECOM
– +
TC
1
TC
2
TC
3
TC
4
Serving – +
Controlling – +
Partnering
FINANCE
– +
FS
1
FS
4
FS
2
FS
3
Serving – +
Controlling – +
Partnering
HEALTHCARE
– +
HC
2
HC
1
HC
4
HC
5
HC
3
Serving – +
Controlling – +
Partnering
PHARMA
– +
PH
1
Figure 3:The four case study triangles.
72 February 2013 ■ Project Management Journal ■ DOI: 10.1002/pmj
A Relational Typology of Project Management Offices
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& Müller, 2003) and that PMOs are transitioning
over time as do the environment
and their organization (Aubry
et al., 2011). This is exactly the point of the
role of the PMO as a leader in knowledge
sharing between different project
management stakeholders. An example
from the Healthcare PMO is the dialogue
that has opened up on process
development between the PMO and
the HR department. The PMO has the
mandate for reviewing almost all clinical
processes within the new hospital
construction project. Process development
was part of the HR department,
which first reacted against the PMO,
but the PMO director managed to
involve the HR department in reviewing
together how this work should be
undertaken in the specific large project
context. They both agreed on a chart,
resulting in the HR department
embarking on the journey with the
PMO. For the PMO director, this is
the only way to succeed in the long term.
This partnering role is not an ad hoc
way of working; it is based on foundations,
such as values and shared vision,
which are pervasive in all their relationships.
The common characteristics of
PMOs in partnership roles, is that they
are parts of the network governance;
they don’t feel the fear, or if they feel
it, they act to pursue their vision and to
influence decision makers and they are
risk taking.
Homework help – Discussion
Within-case analysis indicates that
PMOs within the same organization
show different role profiles when interacting
with different stakeholders. This
becomes evident through the relation
type and the particular position a PMO
occupies within the PMO role triangle.
Cross-case analysis shows that some
PMOs occupy pure roles, whereas others
are more diversified or mixed
in their roles. From these results, four
themes are discussed in more detail in
this section.
Superordinate Type PMO Limits
Knowledge Exchange
A pure PMO role is defined as one
showing a strong expression of one role
and little of the other two roles. From
the three possible pure PMO roles, the
controlling role is the most common
role associated with a superordinate
PMO. It is present in all four case studies,
suggesting that this function prevails
within organizations dealing with
multiple projects. PMOs in superordinate
roles are found at higher levels in
the organizational hierarchy or in
similarly legitimized authoritative positions;
however, the shared commonality
of these PMOs is a lack of learning or
knowledge-sharing mechanisms. These
results are in line with previous empirical
results where control over projects
is compared with the return of the iron
cage, thus giving great emphasis on
controlling projects (Maylor, Brady,
Cooke-Davies, & Hodgson, 2006) over
creativity and innovation (Turner &
Keegan, 2004).
The Pharma PMO is very strong in
controlling and they even do a project
manager performance evaluation,
which influences their career options;
therefore, project managers respect the
PMO and have incentives to be recognized
only for good work performance
and learning activities. They would,
however, not seek the help of a PMO if
the knowledge deficit could be interpreted
as negative.
The two other PMO roles are rarely
found in their pure forms; of those few,
PMOs that show a pure serving role
have a specific expertise and support
the organization through this expertise.
For example, the Local IT PMO from
the Finance case has a coordination
Figure 4: Integrative view on PMO roles.
TC
2
HC
1
Serving – +
Controlling – +
Partnering
Exploration
“slack”
Exploitation
efficiency
– +
HC
2
TC
1
FS
1
PH
1
HC
5
TC
3
FS
4
HC
4
FS
2
TC
4
FS
3
HC
3
February 2013 ■ Project Management Journal ■ DOI: 10.1002/pmj 73
role throughout the whole organization
for major IT projects, while not having
any controlling or partnering function.
Similarly, the country PMO within
the Telecom case strongly supports the
customers at their own site.
Pure partnering is not present at all
and only one PMO shows a pure serving
role. One interpretation of this result
might be that it is difficult for a PMO to
exist with just a partnering role.
Partnering may have to rely on other
complementary roles to exist.
Strengths and Drawbacks on
Diversification in PMO Roles
The strength of the PMO role triangle
resides in its capacity to locate PMOs in
a multidimensional space. Most of the
PMOs within the four case studies do
present diversification in their roles;
this result is in line with the difficulty
of typifying PMOs under a single set of
activities. As shown here, most PMOs
perform more than one single function.
PMOs with diversification may fall into
the four role types. Looking at mixes of
roles, superordinate PMOs are strong in
controlling but also in partnering.
These PMOs adapt their role to different
stakeholders by providing strong
control within strict governance mechanisms
and simultaneously establishing
or participating in learning mechanisms
with regional or local needs. In
our case studies, we did not find a mix
between the controlling role and serving
role within the superordinate PMO.
PMOs with a serving function in a
subordinate role deploy their efforts to
support all project management initiatives
within their organization. These
PMOs participate in others’ partnering
efforts; usually, their legitimacy is fragile.
They are rarely involved in local governance
work. From our case studies,
we see no indication of a combination
of serving function and controlling role
within the subordinate type.
Role diversification may lead to
bureaucracy and political lack of transparency.
This shows up in the Telecom
case study. The global setup supports
tacit and explicit knowledge exchange
across the different layers of the hierarchy.
Speed in communication up and
down the hierarchy is increased
through the intranet-based communication
platform, allowing for both formal
and informal communication
between the PMOs and their project
managers. Formal and informal communication
structures for PMO deployment
and related feedback loops allow
for evaluating the deployment of both
PMO structures as well as project management
practices. Communication
flows are, however, seen as confidential
by PMO members. Although the official
knowledge-sharing structures were
openly discussed, the researchers’
attempts to assess the real data flow in
the PMO hierarchy were denied. The
unwillingness to support the commensuration
of formal and informal structures
indicates possible differences
thereof and “turf fights” at the level of
individual PMOs. To that end, it supports
Ouchi’s (1977) argument for
bureaucratic control structures, based
on norms and reciprocity of the environment,
the legitimate authority of
leaders, plus the acceptance of hierarchy
by the members of the organization,
where information is carried by
rules.
Balanced Type PMO:Resources Slack
and Responsibilities Shift for
Knowledge Transfer to the Individual
There are two elements that merit discussion
regarding the balanced type of
PMO; first, there is the resource slack.
Balanced PMOs occupy the heart of the
PMO role triangle. They are at the equilibrium
of all three roles, not necessarily
with a strong role expression in all
three roles but in at least two of them.
The major characteristics of these
PMOs are:
1. A profound cultural orientation in
performing the three roles. It is like
not having silos between the three
functions. Partnering is present in
controlling as well as in serving roles.
Partnering is the basic approach for
managing stakeholders, not with a
limited number of them.
2. These roles are embedded within the
PMO structure. There are dedicated
resources for performing activities in
partnering within the organization.
These two basic values surround the
balanced PMO; they are part of what
has been identified earlier in this
article as providing resource slack in
the context of PMOs in order to
enhance innovation in project management.
From our case studies, we
found PMOs that have developed
capabilities to interact with a diversity
of stakeholders in different roles.
What seems to be of major importance,
however, is the global orientation
toward partnering.
Second there is the responsibility
shift for knowledge transfer to the
individual. The knowledge flow
between PMOs in this case is complex,
because of its cross-departmental
nature, the span of multiple hierarchical
layers, and the geographic distance.
Informed decision making
across PMOs would require a comprehensive
set of formal meetings and
other structured communication. To
balance the shortcomings of this
potential bureaucracy, the communication
structures are rather open and only
rudimentarily designed, and a “clan”
culture in the sense of Ouchi (1979) is
fostered to shift the responsibility for
knowledge flow for proper decision
making from the bureaucratic “system”
to the individual. Knowledge
sharing is felt as an obligation, a condition
for successful inter-organizational
performance. Through that, the
PMO employees feel responsible for
ensuring information flow and mutual
update across PMOs and hierarchies.
Meetings are held without a formal
manager, and information is shared
through joint documents, extensive
email communication, as well as formal
and informal meetings using all
available media. Balanced PMO roles
increase knowledge sharing but
74 February 2013 ■ Project Management Journal ■ DOI: 10.1002/pmj
A Relational Typology of Project Management Offices
PAPERS
reduce codification and compliance
with standards.
PMO Ambidexterity
From our results, superordinate PMOs
perform mostly a single function of controlling
associated with the search for
more efficiency. In March’s (1991) language
of ambidexterity in learning and
innovation, these PMOs reflect the
rational thinking of exploitation, repeating
what is already known. At the other
end, the balanced PMOs could rather be
associated with exploration, with the
learning within uncertainty. Partnering
calls for being engaged with different
stakeholders in learning from each
other, but at the same time, the balanced
PMOs perform a controlling and serving
role. In this respect, the PMOs may reuse
existing knowledge and adopt a more
rational approach; at the same time, the
balanced PMO should play on exploitation
and experimentation.
The concept of ambidexterity has
also been applied at the individual
level. Aubry and Lièvre (2010) have
used this concept to understand the
project manager competency to combine
and change different management
modes in polar expeditions. This is
exactly what is needed from a PMO, to
combine exploitation and exploration
and, more importantly, to change from
one mode to the other when required.
Conclusion
We can now answer the research question:
What is the nature of PMOs in
terms of relationships within multiPMO
organizations? The PMO is a
multi-role organizational phenomenon,
which adapts to the idiosyncratic
needs of an organization by varying the
expression of their controlling, partnering,
or serving role. This leads to different
relationships with other PMOs and
project management related organizational
entities, in which the PMO is
seen as either superordinate, subordinate,
coequal (respectively), or as balanced
across the three extremes.
To answer this question, we developed
a simple role typology and a
three-dimensional role space that
serves as a tool to capture the complex
relational profiles that PMOs express
with respect to their stakeholders in
empirical practice. The value-add of the
triangular role model is twofold: First, it
reduces the high complexity of PMO
relations into a comprehensive and
simple typological framework and thus
may qualify as a tool for managers in
organizational development. Second,
based on the literature on organizational
learning and innovation and grounded
in four organizational case studies
discussed in this research, the article
suggests that for project management
to enable absorptive capacity and
attain sustainable innovativeness,
PMOs should engage and intensify the
partnering dimension in their overall
role profiles. Although service orientation
(subordinate role profile) and
management orientation (superordinate
role profile) support organizational
effectiveness and exploitation, partnering
creates the slack necessary for
potential exploration.
This research has limitations mostly
due to its explorative nature. The typology
of PMO based on its relationship
with stakeholders will need to be tested
against a larger number of PMOs; therefore,
more quantitative studies for proving
and stabilizing the model presented
here are suggested for the future. In
particular, the partnering role would
benefit from much more examples to
build a foundation of innovation and
slack resources in project management.
The strength of the research lies in the
combination of so far discretely
researched roles into one integrated
model.
More research is needed to enlighten
the role of project management in
innovation, which will also serve the
current critics on the lack of flexibility
found in the project management field.
The contribution to knowledge lies in
the integration of thus far distinguished
roles and is therefore in line with current
methodological trends, which seek
to integrate past dichotomies into new
continua in order to integrate views
toward new and different knowledge
(Teddlie & Tashakkori, 2010). To that
end, it supports Kuhn’s (1996) claim
that new knowledge is created by rather
small paradigm shifts. ■
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Ralf Müller is a professor of project management
at BI Norwegian Business School in
Norway. His principal research interest is leadership
and governance of projects, programs,
portfolios, and PMOs. He is the author or coauthor
of more than 130 publications, and, among
other accolades, the receiver of the 2012 IPMA
Research Award, which he received together
with Monique Aubry and Brian Hobbs, and the
Project Management Journal’s 2009 Paper of
the Year Award. He holds an MBA from Heriot
Watt University and a DBA degree from Brunel
University in the United Kingdom, and a PMP
certification from PMI. Before joining academia,
he spent 30 years in the industry consulting
with large enterprises and governments in 47
different countries for their project management
and governance. He also held related line management
positions, such as the worldwide director
of project management at NCR Teradata.
Johannes Glückler is a professor of economic
and social geography and research fellow at the
Marsilius Center for Advanced Study at the
University of Heidelberg. He received his PhD
from the University of Frankfurt. Previously, he
was a professor of economic geography at the
Catholic University of Eichstätt-Ingolstadt. His
research interests are in the areas of economic
geography, social networks, and service industries.
He has written on relational economic
geography, the geography of knowledge, and
organizational networks in journals such as
Organization Studies, the Journal of Economic
Geography, Regional Studies, and the Service
Industries Journal. He is coauthor of the monograph
The Relational Economy (Oxford
University Press, 2011), which analyzes the
geographies of knowing and learning in the
global knowledge economy.
Monique Aubry, PhD, is a professor in the project
management programs at the School of
Management, Université du Québec à Montréal
(UQAM). Her principal research interest bears on
organizing for projects and organizational
design, more specifically on project management
offices (PMOs). She received the 2012
IPMA Research Award for her research on PMOs
along with Brian Hobbs and Ralf Müller. The
results of her work have been published in
major academic journals and presented at several
international conferences, both research
and professional. She is a member of the Project
Management Research Chair (www.pmchair
.uqam.ca). She is also a member of the
Standards Member Advisory Group and the
Research Informed Standards Steering
Committee of the Project Management Institute.
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PAPERS
February 2012 ■ Project Management Journal ■ DOI: 10.1002/pmj 21
INTRODUCTION ■
T
his article considers the impact of program alignment and related factors
that contribute to successful program delivery. The study
attempted to disclose the key underlying assumptions that connect
program management with related theories of strategic, organizational,
and project management. Exposing the hidden management ideology
and practices that actually inform structure and content requires an
understanding of program success and failure factors (Lycett, Rassau, &
Danson, 2004). The identification of an interaction structure and management
practice that supports continuous alignment may thus provide significant
potential for reducing the unacceptable rate of program failures
(Kotter, 1995; Morris, Crawford, Hodgson, Shepherd, & Thomas, 2006). The
study should be of relevance to professionals who retain or exercise influence
over the formation and execution of programs.
Business strategy is complex and intertwined with all the processes and
systems that are required to effectively manage an organization. Program
management may be considered an effective building block and umbrella
framework in the operationalization of business strategy. The links between
business strategy and program management reside within the alignment of
the strategic processes of formulation and implementation. Strategic alignment
will be unique to a particular organization and will involve a dynamic
and iterative process of mutual adjustment and reshaping (Beer, Voelpel,
Leibold, & Tekie, 2005). Strategic implementation in many companies is an
enigma due to misaligned projects and a lack of a systemic approach to business
strategies.
Understanding the potential contribution of program alignment may
thus further contribute to the improvement of the effectiveness and efficiency
of the delivery of strategic objectives (Burdett, 1994; Chorn, 1991;
Strassmann, 1998). This study has empirically explored implementing strategy
through programs and the need to continually manage program context.
Program management environments are complex, and the uncertainty
that arises from multiple combinations of unique personalities, stakeholder
expectations, assumptions, constraints, changing environments, and human
social systems can provide the impetus for failure (Lehtonen & Martinsuo,
2009). The messy, complex, and multifaceted environment of program management
produces a need to continually realign the program and related
projects to changing environmental and corporate objectives (Thiry, 2004).
Previous research has recommended new directions that focus attention on
causality and complexity in context (Ivory & Alderman, 2005; Morris & Pinto,
2007; Pollack, 2007). The inherent complexity involved in applying structured
program management frameworks to organizational contexts thus warrants
further serious consideration (Pellegrinelli, Partington, Hemingway,
Mohdzain, & Shah, 2007). This study responds to this by applying a dynamic
Successful Programs Wanted:
Exploring the Impact of Alignment
Graeme Ritson, Northumbria University, Newcastle upon Tyne, United Kingdom
Eric Johansen, Northumbria University, Newcastle upon Tyne, United Kingdom
Allan Osborne, Northumbria University, Newcastle upon Tyne, United Kingdom
ABSTRACT ■
Alignment between formulation and implementation
of business strategy can be important for
achieving successful programs. The authors
have explored the development of a program
management alignment theory. Statistical testing
showed that interaction between the study
model variables was found to be multidimensional,
complex, and subtle in influence. Thus,
the authors conclude that programs have both
deliberate and emergent strategies requiring
design and management to be organized as
complex adaptive systems. Program life-cycle
phases of design and transition were often
formed from an unclear and confusing strategic
picture at the outset, which can make those
phases difficult to control. Learning was established
as an underlying challenge. The study
model demonstrated continuous alignment as
an essential attribute contributing toward successful
delivery. This requires program design
and structure to adopt an adaptive posture.
KEYWORDS: corporate strategy; program
management; governance; continuous alignment;
deliberate and emerging strategies
Project Management Journal, Vol. 43, No. 1, 21–36
© 2011 by the Project Management Institute
Published online in Wiley Online Library
(wileyonlinelibrary.com). DOI: 10.1002/pmj.20273
22 February 2012 ■ Project Management Journal ■ DOI: 10.1002/pmj
Successful Programs Wanted
PAPERS
systems perspective to program management.
This may improve the usefulness
and practical application of existing
good practice frameworks (Office of
Government Commerce [OGC], 2007;
Project Management Institute [PMI],
2009).
Theoretical Background
and Model
The study was operationalized through
the core concepts of systems, governance,
innovation and learning, corporate
strategy, environmental factors,
continuous alignment, and successful
delivery (Figure 1). This viewed success
as a multidimensional construct—
program management success, program
success, achieving business objectives,
strategic orientation, and business success
(Shenhar, Dvir, Levy, & Maltz,
2001). These dimensions consider success
from a business, corporate, and
economic level, respectively. Appropriate
hypotheses were advanced to
formulate a reasonable prediction
about the relationship of the variables
contained in the model.
Corporate Strategy, Project, and
Program Management
Program management is strategic in
orientation through delivering outcomes
and benefits related to the organization’s
strategic goals (Association
for Project Management [APM], 2007a;
OGC, 2007; PMI, 2009). This will require
the program and interrelated projects
to have their objectives and strategies
aligned with corporate strategy to create
an iterative hierarchy that develops
into business operations (Dietrich &
Lehtonen, 2005). Some organizations
may be adopting program management
as they develop their strategic
management capability. There will be a
multiplicity of options available in
achieving strategic objectives through
program-driven approaches requiring
intelligent program design. Context will
be crucial in determining appropriate
program formation (Pellegrinelli, 2002;
Pellegrinelli et al., 2007). International,
government, societal, industrial, commercial,
and business programs will
differ in focus and predictability of outcome.
Clearly articulated corporate strategy
will support the prioritization and
execution of the right programs and
projects. This alone will not guarantee
program success. Ill-conceived business
strategy will not necessarily be
redeemed by program and project
management. This will make reliable
prioritization and consistent allocation
of resources based on the greatest
strategic contribution more difficult
(Hrebiniak, 2006). Programs may also
be compromised by strategic business
case misrepresentation. This will result
in misalignment with strategic objectives.
Managing programs will involve
the task of remaining aligned with corporate
strategy (OGC, 2007).
Some organizations have welldeveloped
program management
maturity and organizational management
systems that support continuous
alignment. Well-aligned organizations
will be able to prioritize both activities
and how identified work gets executed.
The greater the alignment between the
operating environment, strategy, structure,
and processes, the more positive
H1. Corporate strategy
H6. Continuous
alignment
H2. Internal and external
environments
H4. Systems, subsystems,
and processes H3. Successful delivery
H5. Program
governance
H7. Learning and
innovation
Figure 1:Theoretical model and hypotheses.
February 2012 ■ Project Management Journal ■ DOI: 10.1002/pmj 23
effects this will have on performance
(Middleton & Harper, 2004). Alignment
will be essential for strategic success,
although nonalignment may exist for
temporary periods through significant
organizational and industry-sector
change. Strategy formulation and
implementation will thus require organizational
alignment with its resource
capability (Engwall & Jerbrant, 2003).
Shenhar et al. (2001) also suggested
that project success will be strongly
linked to an organization’s business
effectiveness.
Research indicates that project failure
is distinctly linked to factors at the
front end of a project through misalignment
with an organization’s key strategic
priorities (Pinto & Slevin, 1998). Hyvari
(2006) and Engwall (2003) supported
this in concluding that organizational
context will be an important factor
in determining success or failure.
Programs should be selected and
formed from organizational strategy by
aligning and coordinating related projects
(Morris & Jamieson, 2005). Program
formation and structure may be unclear
at the outset, requiring flexible
strategic implementation planning and
modular phased projects. This need for
a dynamic interface provides a clear
business case for organizations to
improve their capability in the management
of programs of projects and to
ensure that structure follows business
strategy. These and other contextdependent
and decision-oriented
issues lead to the following hypothesis:
H1: Corporate strategy leads to a
vision and stakeholder strategy that
takes account of the organization,
market, and sector in which it operates.
Environmental Factors
Modern organizations are constantly
analyzing their business activities and
industry sector, searching for business
opportunities (Venkatraman, 1989).
This may result in constant change of
business priorities and plans. De Wit
and Meyer (2005) argued that the most
common cause of corporate failure is
misalignment between the organization
and its environment. Sheppard
and Chowdhury (2005) strengthened
this argument and emphasize that a
fundamental failure of management
will exist if they do not properly evaluate
the environment. Globalization and
technological innovation create dynamic
and complex environments for many
current businesses where change is
a constant factor. Managing major
changes successfully may require an
organization-wide approach, and this
will impact at both the operational and
strategic levels (Carnall, 2007). The size
and scale of some organizations make it
impracticable for a radical change from
existing practices to be orchestrated at
the same time. Strategic change decisions
must be oriented in the most
appropriate sequence to increase the
likelihood of execution success (Bruch,
Gerber, & Maier, 2005). The OGC (2008)
recommended the adoption of program
and project prioritization categories to
ensure alignment between business
priorities, current capability, and
capacity to deliver.
Well-constructed and well-managed
programs should provide confidence
that the right projects are being sponsored
and that the desired benefits will
be achieved. Managing a program
will be a complex undertaking requiring
both project management acumen
and the capability of a business leader
(Pellegrinelli, 1997). Every program will
be unique to its contextual environment.
Rapidly changing and chaotic
environmental factors will create a high
level of task and organizational complexity.
This will require the impetus to
monitor and challenge program and
project performance. Increasing program
complexity may provide an ever-present
threat of failure. Solving one unyielding
problem may create unexpected drawbacks
elsewhere. The more complex the
program, the greater interaction risk and
interdependence with the internal
and external environment (Verma &
Sinha, 2002). This will necessitate a focus
on the tension between strategic direction,
project delivery, operational effectiveness,
and external influences. The
organization is unlikely to be in total
alignment and will have different
change capabilities. An open outlook
and sense of cooperation would be
ideal but this is seldom realized in practice
(Kotter & Schlesinger, 2008).
Organizational change resistance will
be inherent (Ford & Ford, 2009). The
program will more than likely be differentiated
and gradual rather than radical
and coordinated.
Knowledge of the current and future
environment will influence the choice of
strategic objectives and strategies
employed. Changes to the organizational
and business environment may lead
to significant alterations to the program
scope and priorities. The time horizon
and long-term nature of some programs
can have a significant impact on manageability.
The speed of technical evolution
and communication technology
may require adjustment or even cancellation
of tight-time-frame programs.
The program’s mission should provide a
focus for an integrated continuous decision
alignment framework (Scherpereel,
2006). Major strategic reviews may be
required at different times in the
program’s life cycle to coordinate alignment.
This will be an indicator of organizational
strategic maturity (APM,
2007b). Unpredictable environmental
factors are thus cross-linked to managing
programs and will require a dynamic,
flexible, and adaptive temporary
organization. Program management in
practice will involve top-down strategic
implementation linked with bottom-up
emerging management strategy through
successful project integration in the
host organization (Srivannaboon &
Milosevic, 2006). These emergentshaping
conjectures lead to the following
research hypothesis:
H2: The organization’s strategy is
influenced and reshaped from both
the internal and the external environments.
24 February 2012 ■ Project Management Journal ■ DOI: 10.1002/pmj
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Systemic Factors
Program management is a management
strategy informed by complexity
thinking, which increases manageability
and coordination. Deliberate and
emergent business strategies will
require flexibility in the program design
(Elizabeth & Ysanne, 2007; Mintzberg,
1994; Mintzberg, Ahlstrand, & Lampel,
1998; Mintzberg & Waters, 1985).
Emergence describes a dynamic
process that is the product of ongoing
system interactions. This refers to the
coexistence and impact of program
management, project management,
business-as-usual activities, environmental
factors, and corporate governance.
The emergent and coevolutionary
dynamic of program management will
require open systems. Open system
refers to the uncontrollable variable of
the environment and the self-organizing
tendency if left unmanaged. This introduces
nonlinear interaction, unpredictability,
and feedback loops in support
of organizational learning theory.
Open systems theory considers the
organization as a number of interdependent
subsystems that are open to
and connected with their environment.
This provides the potential for the
system to take on a new form in
response to environmental factors
requiring the facilitation of informationdriven
activities.
Program management provides an
integration solution for strategic business
management in dealing with
complexity and chaos in multiproject
environments (Pourdehnad, 2007).
Establishing systemic alignment
between people, processes, and technology
will provide benefits. Emerging
technologies can be adopted to enhance
organizational alignment capability and
maturity (Gaddie, 2003). The program
system may be radically unpredictable
beyond its immediate future, requiring a
dynamic approach of emergent planning
(Kash & Rycoft, 2000). The capability
of an organization and the coordinated
presence of critical program elements
will influence integration success.
Critical program elements refer to the
contextual program design or blueprint.
Established program processes
will need to continuously integrate
adaptive decision making through
learning processes (Lindkvist, 2008).
This will require a focus on complex
interactions, interdependency, processes,
and the coevolution of business
systems.
Understanding what management
practices are required for any given program
will be an important challenge. It
will be fundamentally important that
the distinguishing features of the program
are understood, as this should influence
program design (Meyer, Loch, &
Pich, 2002). Uncertainty (structural,
technical, directional, and temporal)
will be inevitable and a basic feature of
this complex system. Leading a program
will thus be multifaceted, situational,
and transient (Uhl-Bien, 2006).
Contextual uncertainty may materialize
in the form of an opportunity or risk.
High uncertainty and complexity will
require a holistic approach in designing
the program (Maylor, Brady, CookeDavies,
& Hodgson, 2006). Influences
from the external environment may be
frequent, accidental, and unpredictable,
with the internal environment
being equally as dynamic (Rybakov,
2001). Drawing together these system
dynamic principles leads to the following
research hypotheses:
H3: The program mission and objectives
support the creation of worthwhile
business benefits and the
successful delivery of the program.
H4: Programs and projects are managed
through a set of interdependent
critical processes and subsystems
that support strategic alignment and
realignment.
Governance
Corporate governance provides the
structure for initiating and determining
the objectives of an organization and the
means of monitoring, evaluating,
and influencing performance. Effective
program governance will be a major
strategic factor and cannot be confined
to a narrow static model that ignores
dynamic complexity. This will require
emphasis toward flexibility with the
organization-program-governance interface
(Rycroft & Kash, 2004). The sponsoring
group will be pivotal for success.
A further critical aspect will be the
determination of structures and control
measures to ensure alignment with
the unique organizational and contextual
environments. The success of the
program will require a flexible governance
structure that can be identified
from contextual design criteria to
ensure that it is fit for purpose. The
program mission will be a critical reference
point for aligning structures,
policies, procedures, behaviors, and
decision making.
Multiowned program governance
will require a strong focus on alignment
(APM, 2007b). This will be derived from
intertwining multiple perspectives of
governance in establishing a self-organizing
complex adaptive system (White,
2001). Various alignment strategies may
be needed in response to stakeholder
objections and agenda-setting behaviors.
Emergent and ill-defined programs
will need to make greater use of alignment
mechanisms and tools. Welltimed,
accurate, and focused reporting
will be central to integrating both performance
and learning loops. These
attributes provide the essential platform
for configuration activities in the
process of actively shaping and reactively
adapting to the shifting contextual
environment. These issue and problembased
suppositions lead to the following
research hypotheses:
H5: Program governance provides
the control framework through
which the objectives are delivered
while remaining within corporate
visibility and control.
H6: A continual process of realignment
ensures that programs and projects
remain linked to corporate objectives
and environmental influences.
February 2012 ■ Project Management Journal ■ DOI: 10.1002/pmj 25
Innovation and Learning
Organizational learning is essentially
about an organization increasing its
ability to explore opportunities and
undertake effective action (Carlile,
2004). This may lead to far-reaching
changes and the formulation of new
organizational strategies. Learning and
continuous improvement is attributed
as the highest level of management
maturity. There must be defined roles,
functions, and procedures for learning
to become organizational (Lipshitz,
Popper, & Friedman, 2002). The various
bodies of knowledge incorporate the
need to learn from projects. Learning
through programs and projects is thus a
subset of organizational learning
(Brady & Davis, 2004). This will need
the systemic integration of data, information,
and knowledge. Sense (2007)
suggested that projects are an embryonic
structure that develops a new
community of practice through situational
learning and negotiation of
emergent opportunities. This provides
an experientially constructed temporary
system for solving problems and
knowledge transfer.
Learning from both success and
failure will thus be essential in a program
of projects. Programs provide
enhanced opportunity for learning
through the batching of related projects,
interdependency, and the
increased socialization from resource
sharing. Project management practices
will differ between industry sectors and
organizations, providing a potential
gulf in language and learning that must
be considered. The ill-defined requirements
of some programs will challenge
the linear stage-gate process of innovation
through inherent iteration (Smith &
Winter, 2005). Programs may require
differing distinctive leadership styles at
different junctures in the program life
cycle. Multidisciplinary learning will
emerge through a process of activity
and alignment decision making (Fong,
2003). The following research hypothesis
captures this strong learning relationship:
H7: Within the life cycle, program
and project processes embrace
change and realignment by using
learning to create innovation and
improvement opportunities to support
the successful delivery of the
program.
Method
The study was designed to bring to the
forefront critical issues that supported
the advancement of alignment theory
for program management. The need for
a rigorous theory-building process led
to the selection of a mixed-method
study design that involved both statistical
and text analysis.
Sample and Data Collection
The participants were selected from
a population profile that was established
from the Rethinking Project
Management Network, accredited project
management training and consulting
organizations, the e-mail list for the
Association for Project Management
Programme Management Specific
Interest Group, and specific e-mail
groups from a UK-wide service-led
organization. The Rethinking Project
Management Network was a UK government-funded
research initiative that
aimed to develop, extend, and enrich
mainstream project management ideas
in relation to developing practice. This
included leading academics and practitioners
in the field of project management.
The program concluded with five
directions established for future
research, which were outlined in a 2006
special issue of the International Journal
of Project Management. These themes
complemented this study through a
growing emphasis on programs and
managing collections of projects.
Association for Project Management
Accredited Project Management training
providers specialize in the delivery of
project-based training that is aligned to
APM qualifications. These companies
influence developing practice and project
professionals through their consultancy
practice. The APM Programme
Management Specific Interest Group
aims to be the leading internationally
recognized group for program management.
This study contributed to their
mission to promote the science and discipline
of program management. The
specific e-mail groups from the serviceled
organization consisted of those
involved in both transformational
change and information system programs.
All respondents were further
classified by their role within programs
and the context of their practice-related
experience. This targeted professional
groups who were classified as consultants
or experts, senior managers that are
actively involved in programs, program
managers, project managers, and those
holding project-related job functions.
This ensured the respondents were representative,
knowledgeable, and appropriate
to the study.
Data collection was by means of a
standardized questionnaire and semistructured
interviews. The quantitative
data was collected through a multimode
administration method primarily
from an e-mail-driven strategy supported
by a web survey. The web survey
mirrored the self-administered questionnaire.
This did not include advance
notification, as it was administered
through the Programme Management
Significant Influence Group monthly
newsletter. The e-mail-driven list consisted
of 264 subjects, while the web
survey provided 2,005 additional subjects.
Six volunteer informants were
randomly selected for interviews that
classified themselves as either program
consultants or experts and program
managers to ensure absolute knowledge
of the dynamics of the study model.
Each interview volunteer further represented
a different program management
context—information technology,
organizational change, new product
development, civil engineering, and
someone who had diverse experience
with different types of programs. These
interviews further explored the causal
relationships of the research model to
understand how participants actually
constructed theory and determined
26 February 2012 ■ Project Management Journal ■ DOI: 10.1002/pmj
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emerging phenomena in relation to the
study. This provided the opportunity for
the interviewee to introduce issues that
they conceived as important. The quantitative
and qualitative phases were
integrated by an iterative process, with
each influencing the other accordingly.
Measures
The questionnaire design was structured
to gather information and understanding
about organizational, environmental,
program, and project management
alignment. Respondents were requested
to respond based on their practicerelated
experience and expertise. This
required questions to be answered by
respondent experience and insight.
Closed-ended questions were used to
classify the professional orientation
(program management consultant/
expert; senior manager involved in programs;
program manager/director;
project manager involved in programs;
other—please specify) and program
management context of participants
(IT/software development; organizational
or management change; new
product development; construction/
civil engineering; generalized). These
differing characteristics and attributes
were coded by a five-category nominal
level of measurement. The model variables
and hypotheses were included in
the questionnaire as closed-ended
questions to validate the respondent’s
opinion of the statements. These were
measured on a four-point Likert scale
ranging from 1 (never) to 4 (always).
This was a deliberate decision in
removing the availability of a middle
alternative to ensure respondents indicated
the direction of their viewpoint.
The model variables and hypotheses
needed to be constructed into a
structural equation model to test and
confirm proposed relationships. This
involved translating the proposed
alignment theory into a structural
model. Learning and innovation, program
governance, and systemic factors
were classified as independent variables
in the study model. Successful
delivery was the dependent variable,
which was hypothesized to be influenced
by the independent variables
and intervening variables of environment,
continuous alignment, and corporate
strategy. The general sample
characteristics and size of the study
data determined the measurement and
interpretation of the statistical analysis.
The selection of structural equation
modeling ensured that measurement
error was taken into account in the procedures
(Schumacker & Lomax, 2004).
The model was identified by including
an error parameter for each variable
that fixed the factor loading to 1.
This multivariate statistical approach
combined the application of both
path and confirmatory factor models in
analyzing the causal model and study
data. Analysis of Moment Structures
(AMOS) is an add-on module for SPSS
that allows structural equation models
to be specified by using a simple dragand-drop
drawing tool to test proposed
causal relationships. The specified
structural model follows standard
drawing conventions to show the causeand-effect
relationships (Figure 2). The
variables measured in the study model
are depicted by enclosed rectangles.
Unobserved variables or model measurement
errors are denoted by circles.
This ensured that measurement errors
were explicitly considered in statistical
calculations. Straight-line singleheaded
arrows from one variable to
another indicate a direct influence
from that variable to the other. Zero rating
values would indicate that there
was no direct impact. The absence of a
straight-line single-headed arrow
between variables indicates that there
are no direct effects hypothesized.
Double-headed curved lines between
variables indicate a covariance. These
coefficients detect and measure the
relationship between two variables
through an index range, with zero indicating
no relation and 1.0 suggesting a
perfect relationship. The strength and
impact of each model parameter estimate
is illustrated by the numerical output
beside an arrowhead or variable in
the study model. Problems in specifying
Study Variable
Study Variable
Parameter value Error
indicating no relation
Parameter value
indicating a perfect relationship
1.0
0.0
Circle used to draw
the unobserved
variables/model
measurement error
Study Variable
Single-headed arrows
used to draw the causeeffect
relationship
between variables
Rectangle used to draw
the study variables
Double-headed arrow
used to draw the
covariance between
variables
Error
Error
Figure 2: Structural equation model drawing conventions.
Note. Model measurement error factor loading fixed to 1.0.
February 2012 ■ Project Management Journal ■ DOI: 10.1002/pmj 27
the drawn model structure are highlighted
by an error message or by the
AMOS text output not calculating.
Measurement and study model modification
involved identification with and
linking of qualitative data.
Reliability and Validity
The mixed-method study design combined
the different criteria used for
validity and reliability in both qualitative
and quantitative research. There
were a number of prerequisites that
needed to be satisfied before a multivariate
analysis could be undertaken.
Exploratory data analysis validated the
appropriateness of statistical methods
and techniques (Table 1). Kurtosis outputs
established that outliers in the
data sample were not problematic, as
this can provide misleading values with
statistical methods and techniques. The
presence of outliers would affect structural
equation model fit significance tests.
The Pearson’s correlation coefficient
and two-tailed significance-level tests
indicated that all variables were significantly
correlated. Correlation is a
measure of linear dependence between
variables. The stronger the correlations,
the more power structural equation
modeling has to detect an incorrect
fitting model. Reliability testing
provided an indication of the general
quality of the study data. The
Cronbach’s alpha statistic (1951) was
adopted as a measure of the internal
consistency and reliability of the study
data. This statistical output is from any
value less than or equal to 1 and provides
an unbiased estimate of the ability
of the data to be generalized. The
value of above 0.70 is recommended,
although values exceeding 0.80 are
desirable for higher reliability test studies.
The Cronbach’s alpha statistic output
of 0.831 thus validated that the
internal consistency reliability of this
analysis was good. The exploratory
data analysis procedure concluded that
the data were approximately multivariate
normal in distribution and suitable
for application to structural equation
modeling. This classification was
essential, as small deviations from
multivariate normality can lead to a
large difference in the Chi-square test.
AMOS labels this test global model fit
(CMIN). This label will now be adopted
throughout the remainder of this article
when referring to the Chi-square test.
Multiple pilot-testing methods
were used to refine the standardized
questionnaire and qualitative interview
structure to validate that the designs
were clear, simple, and elicited the
appropriate responses. Missing data
were eliminated with participants of
the online survey by adopting a computer
questionnaire, which needed a
response before completing the survey.
The quality and completeness of the
returned e-mail questionnaires was
extremely high. The only incidence of
missing data was clarified by a follow-up
0 2 3 4 5 6 7 Mean SD
Strategy Correlation 0.407** 0.402** 0.366** 0.360** 0.441** 0.386** 2.89 0.695
Sig. (two-tailed) 0.000 0.000 0.000 0.000 0.000 0.000
Environment Correlation 0.297** 0.309** 0.301** 0.403** 0.336** 3.23 0.673
Sig. (two-tailed) 0.002 0.001 0.001 0.000 0.000
Successful Delivery Correlation 0.503** 0.485** 0.442** 0.454** 2.93 0.726
Sig. (two-tailed) 0.000 0.000 0.000 0.000
Systemic Factors Correlation 0.490** 0.453** 0.406** 2.89 0.782
Sig. (two-tailed) 0.000 0.000 0.000
Governance Correlation 0.531** 0.354** 2.89 0.758
Sig. (two-tailed) 0.000 0.000
Continuous Alignment Correlation 0.522** 2.70 0.761
Sig. (two-tailed) 0.000
Learning and Innovation Correlation 2.50 0.751
Sig. (two-tailed)
Cronbach’s Alpha Reliability Statistics Based on Standardized Items 0.831
**Pearson’s correlation is significant at the 0.01 level (two-tailed).
Table 1: Pearson’s correlation and Cronbach’s alpha reliability tests.
28 February 2012 ■ Project Management Journal ■ DOI: 10.1002/pmj
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e-mail. Structural equation modeling
used interval data from the questionnaire
for testing purposes. Randomized
selection was adopted for the interview
informants to address the amount of
diversity bias evident from the quantitative
data phase. This ensured that a
representative sample could be generalized
across the wider program management
community. The semistructured
interviews focused on rigorous subjectivity
by respondent validation of the
quantitative research findings. This
involved asking questions such as
“Does the model structure make
sense?” and “Are the relationship paths
representative of your experience?”
Respondents were then encouraged to
justify opinions and provide alternative
explanations. This facilitated understanding
and interpretation of relationships
between study variables.
Structural equation modeling validation
essentially involved statistical
and theoretical evaluation of model fit.
The selection of appropriate statistical
fit measures considered issues such as
sample size and overall complexity of
the model. These tests are based on the
assumption that the correct and complete
relevant data have been modelled.
The study sample size adopted a
lower limit of 100 respondents as proposed
by some authors (Chen, Bollan,
Paxton, Curran, & Kirby, 2001; Gagne &
Hancock, 2006). Unobserved error variables
were included to explicitly depict
the unreliability of measurement in the
model. This allows the structural relations
between variables to be accurately
estimated. Research Topics – Criteria for study model fit
and testing were determined from the
size of the study data and sample multivariate
characteristics. Model validation
was determined through global
model fit (CMIN), root mean square
error of approximation (RMSEA), goodness-of-fit
index (GFI), and other normalized
model fit measures. CMIN of
zero illustrates a perfect model fit,
although it is generally accepted that
this is impractical in reality. For reasonable
sample sizes, a difference enough
to produce a CMIN in the region of the
degrees of freedom (DF) would suggest
a close model fit. RMSEA was adopted
because it provides an output that
does not penalize model complexity.
Modification index results following a
specification search illustrated the reliability
of the relation paths drawn in a
specified structural equation model.
Data Analysis
Study model modification followed an
iterative process between the structural
equation modeling statistical analysis
(Arbuckle, 2007) and model structure
theoretical validation through semistructured
interviews (Silverman,
2006). The best-fitting model that was
also consistent with theory was selected.
Structural equation models combine
measurement models (e.g., reliability
tests) with structural models (e.g.,
regression weights). This is based on
data-driven model fitting. AMOS provided
automated modification indices
as an alternative to manual model
building and model trimming. Model fit
was first measured on the closeness of
the study-sample variance-covariance
matrix. Modification needed to satisfy
these measurement criteria and also
meet the need for theoretical meaningfulness.
Statistical model cross-validation
through semistructured interviews
established problems in the structure of
the model. This resulted in the model
structure being redefined with the variables
arranged differently, affecting
path relations (Figure 1).
The model estimates were then
recalculated. This involved the AMOS
automated modification function, indicating
that all the model correlations
and direct relations from the independent
variables to the intervening variables
were optional. This supported the
potential of further model refinement by
removing poorly weighted relationship
parameters following the specification
search. This provided a multiplicity of
other models that fitted the data and
identified potential adjustments that
could be made to the model. The AMOS
text output indicated the estimated
change and reliability in the new path
coefficient for each alternative model
proposed. Improvement in model fit
was measured by a reduction in CMIN.
The statistical model output indicated
that overall model fit was adequate and
could not be further statistically
improved (Table 2 and Figure 2). The
model structure was then further
refined to provide a theoretically validated
model. This introduced a new
variable that could not be statistically
measured.
Results
The e-mail survey provided a response
rate of 31% (81). The web survey had a
larger population but significantly
lower response rate of 1% (29), reducing
the overall study response rate to 5 percent
(110). This provided some concern
regarding statistical significance.
Various studies have concluded that a
lower response rate does not necessarily
differentiate reliably between accurate
and inaccurate data (Keeter,
Kennedy, Dimock, Best, & Craighill,
2006; Visser, Krosnick, Marquette, &
Curtin, 1996). The findings of these
studies found that much lower
response rates were only minimally less
accurate. The 29 web survey respondents
were included, as they provided a
rich source of expert data. More importantly,
their responses also enhanced
the sample size to improve statistical
model significance. Survey respondents
were reasonably dispersed over
four program management practicerelated
groups—experts (25%), senior
managers (27%), program managers
(21%), and project-related roles (27%).
An evaluation of Hoelter’s (1983) critical
N from the model output suggests
that the largest model sample size
required at a significance level of 0.05 is
a threshold of 37. This provided reasonable
confidence of sample-size adequacy
(N 110) against concerns of statistical
significance.
The statistically modified model
is illustrated in Figure 3 following
February 2012 ■ Project Management Journal ■ DOI: 10.1002/pmj 29
Parameter Standardized
Description of Path Estimate SE CR P Estimate
Environment d Governance 0.134 0.091 1.473 0.141 0.151
Environment d Systems 0.124 0.090 1.378 0.168 0.144
Environment d Learning 0.201 0.087 2.293 0.022 0.224
Alignment d Systems 0.122 0.084 1.457 0.145 0.125
Alignment d Environment 0.191 0.088 2.171 0.030 0.169
Alignmentd Governance 0.312 0.084 3.705 *** 0.311
Alignment d Learning 0.308 0.082 3.741 *** 0.304
Strategy d Environment 0.233 0.093 2.515 0.012 0.226
Strategy d Alignment 0.160 0.099 1.621 0.105 0.175
Strategy d Governance 0.086 0.092 0.932 0.352 0.094
Strategy d Systems 0.101 0.087 1.167 0.243 0.114
Strategy d Learning 0.129 0.090 1.436 0.151 0.140
Successful delivery d Environment 0.084 0.102 0.826 0.409 0.078
Successful delivery d Alignment 0.293 0.091 3.201 0.001 0.307
Successful delivery d Strategy 0.246 0.100 2.454 0.014 0.236
Table 2: Regression weights and standardized regression weights.
Program governance
Systemic factors
Learning and innovation
Environment
Continuous alignment
Corporate strategy
0.57
e1
1
0.61
e2
1
0.56
e3
1
Successful delivery
0.37 e4
0.32
e5
e6 0.34
1
1
1
0.12
0.23
0.19
0.16
0.08
0.29
0.25
0.13
0.31
0.12
0.10
0.20
0.13
0.31
e7 0.39
1
0.24
0.29
0.20
Program Management Alignment Theory
Chi-square 23.156 (3 df)
p 0.000
0.09
Figure 3: Statistically modified structural equation model.
30 February 2012 ■ Project Management Journal ■ DOI: 10.1002/pmj
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PAPERS
measurement model reliability testing.
An analysis of the number of distinct
parameters (NPAR 25) and the number
of degrees of freedom (DF 3)
determined that the model was complex.
This outcome will provide conflicting
results with some model fit
measures that attempt to balance parsimony
or simplicity against model
complexity. RMSEA provides an output
that does not penalize model complexity.
The modified model has an output
of 0.248 that exceeds the reasonable
error approximation of 0.1 suggested by
Browne and Cudeck (1989). This suggests
poor model fit, although RMSEA
can be misleading when the minimum
sample discrepancy function (CMIN/
DF) is small and sample size is not large
( 200). Figure 3 illustrates the modified
model, which provides an adequate
CMIN of 23.156, with the minimum
sample discrepancy function
being satisfactory (CMIN/DF 7.719).
The minimum sample discrepancy
function (CMIN/DF) attempts to make
CMIN less dependent on sample size.
The minimum sample discrepancy
function (CMIN/DF) should be close to
1 for perfect fitting models. CMIN for
models involving 75 to 200 cases are a
reasonable measure of model fitness.
However, complex models are more
likely to have a good CMIN. The p values
for CMIN for sample sizes less than
200 are also useful as this measure is a
function of sample size (p 0.000).
Other measures of model fit were
considered in addition to the CMIN
standard. The objective was to find the
most parsimonious model, which was
well fitting by a selection of GFI tests.
Comparison against a baseline model
allows a further evaluation against the
saturated (e.g., guaranteed to fit any set
of data perfectly) and independence
(e.g., severely constrained to provide a
poor fit) models through a number of
indices. These fitness measures are normalized
to fall between 0 and 1, with an
output close to 1 indicating a good fit.
Jöreskog and Sörbom’s (1984) GFI supports
this outcome of good model fit
(GFI 0.948). The Bentler-Bonett
(1980) normed fit index (NFI) further
suggests a good model fit (NFI 0.900),
although results less than this value
indicate that substantial improvement
is required. Bollen’s (1989) incremental
fit index (IFI) and Bentler and Weeks’
(1980) comparative fit index (CFI) both
indicated a very good model fit (IFI
0.912 and CFI 0.904).
Parsimony-adjusted measures provide
an estimate of the required parameters
to achieve a specific level of model
fit. This rewards parsimonious models
with relatively few parameters to estimate
in relation to the number of variables
and relationships in the model.
Some researchers oppose penalizing
models with more parameters. There is
no commonly agreed-upon cut-off
value for an acceptable model,
although some authors use above 0.50
and others 0.60 (Preacher, 2006). The
James, Mulaik, and Brett (1982) parsimonious
normed index (PNFI 0.129)
and parsimonious comparative fit
(PCFI 0.129) suggest poor model fit.
These results are influenced by model
complexity. This measure of fit thus
offers little in contributing to the selection
of the best-fitting model other than
for assessment after consideration of
goodness-of-fit measures among proposed
competing models.
Path correlation coefficients in the
model were interpreted after a well-fitting
model had been accepted.
Regression weight significance tests for
each parameter relationship in the
structural model are given in Table 2.
The first column is labelled Parameter
Estimate (PE), with the next column
indicating the Standard Error (SE) for
each parameter. The Critical Ratio (CR)
is the parameter estimate divided by
the SE. Any critical ratio that exceeds
1.96 in size would be identified as significant,
using a significance level of
0.05. The SE is only an approximation
and therefore may not be the best
approach in determining parameter
significance, and caution was used in
its interpretation. Individual parameter
values can also be affected by sample
size, with Anderson (1984) recommending
that sample sizes exceed 150
for reasonable and stable parameter
relationship estimates. Structural path
coefficients are the effect sizes calculated
by AMOS. These are displayed above
their respective arrows in the structural
drawing diagram (0.8: high, 0.5: moderate,
less than 0.2: low).
All correlation coefficients for the
variables that represent the critical program
elements are positive in direction
and have moderate strength (0.20 to
0.29). The CRs for each of these are statistically
significant (CR 3.927, 4.595,
and 3.487). This indicates that there is a
closely defined relationship between
the critical program variables, suggesting
a finely balanced direct correlated
effect on the intervening variables. The
continuous alignment intervening variable
is directly influenced the greatest
from the collective strength of all the
independent variables (0.31, 0.12, and
0.31). Both the governance and learning
and innovation variables are
deemed statistically significant (CR
3.705 and 3.741, respectively), although
the systemic variable is insignificant
(CR 1.457, p 0.145). The dominant
independent program variable in relation
to strength impact is learning and
innovation (0.13, 0.31, and 0.20)
The relationship paths from the
environment variable to continuous
alignment and strategy are both statistically
significant (CR 2.171, p 0.030
and 2.515, p 0.012, respectively).
The environment variable has a direct
(CR 0.826, p 0.409) and indirect
effect on the successful delivery dependent
variable through both the continuous
alignment and corporate strategy
intervening variables. Continuous
alignment also has a direct (CR 3.201,
p 0.001) and indirect effect on the
successful delivery dependent variable
through corporate strategy. Continuous
alignment and corporate strategy have a
moderate direct individual effect but a
strong collective influence on successful
delivery (0.29 and 0.25, respectively).
February 2012 ■ Project Management Journal ■ DOI: 10.1002/pmj 31
The environment variable has a low
direct impact on successful delivery
(0.08) but moderately contributes indirectly
through two other intervening
variables (0.19 and 0.23). Table 3 further
summarizes the testing of hypothesized
relation pathways in the accepted
study model (CR 1.96, significant at
the p 0.05 level).
The findings of the statistical investigation
suggest that the independent
variables are predicators of successful
program delivery through the complex
interaction of the intervening variables.
The outcome of the analysis illustrates
that the model is complex, with relationships
among indicators precariously
balanced. The modified model offers
an empirical explanation of the critical
relationships involved for continuous
alignment and successful delivery. The
results of this mathematical maximization
procedure are sample-specific and
can only be generalized to the study
population. This provides a causal
model that articulates but does not
conclude causal assumptions. The
semistructured interviews further validated
the relationship and importance
of the statistical analysis impact
weighting for each parameter. An
underlying theme that emerged from
each interview was the need to make
more clearly explicit the activity of program
design. This provided a strong
justification for the importance and
inclusion of program design in the
study model. The inclusion and visibility
of this variable were further supported
by expanding the necessary dynamic
feedback from corporate strategy.
The model structure was revised
accordingly (Figure 4). Quantitative
data had already been gathered, so the
modified and theoretically validated
Path Coefficients Critical
Description of Relationship Path (Estimate) Ratio (CR) p-value Result
H1 Successful delivery d Strategy 0.246 (Moderate) 2.454 0.014 Significant
Design d Strategy No data No data No data Untested
H2 Alignment d Environment 0.191 (Low) 2.171 0.030 Significant
Strategy d Environment 0.233 (Moderate) 2.515 0.012 Significant
Successful delivery d Environment 0.084 (Low) 0.826 0.409 Insignificant
H3 Successful delivery d Strategy 0.246 (Moderate) 2.454 0.014 Significant
Successful delivery d Environment 0.084 (Low) 0.826 0.409 Insignificant
Successful delivery d Alignment 0.293 (Moderate) 3.201 0.001 Significant
H4 Environment d Systems 0.124 (Low) 1.378 0.168 Insignificant
Alignment d Systems 0.122 (Low) 1.457 0.145 Insignificant
Strategy d Systems 0.101 (Low) 1.167 0.243 Insignificant
H5 Environment d Governance 0.134 (Low) 1.473 0.141 Insignificant
Alignment d Governance 0.312 (Moderate) 3.705 *** Significant
Strategy d Governance 0.086 (Low) 0.932 0.352 Insignificant
H6 Strategy d Alignment 0.160 (Low) 1.621 0.105 Insignificant
Successful delivery d Alignment 0.293 (Moderate) 3.201 0.001 Significant
H7 Environment d Learning 0.201 (Moderate) 2.293 0.022 Significant
Alignment d Learning 0.308 (Moderate) 3.741 *** Significant
Strategy d Learning 0.129 (Low) 1.436 0.151 Insignificant
H8 Learning d Design No data No data No data Untested
Systems d Design No data No data No data Untested
Governance d Design No data No data No data Untested
Table 3:Tests of hypothesized relationship pathways (p-value 0.05).
32 February 2012 ■ Project Management Journal ■ DOI: 10.1002/pmj
Successful Programs Wanted
PAPERS
model could not be statistically tested
further.
Homework help – Discussion
The study was designed to advance the
development of an alignment theory for
program management through a rigorous
theory-building process. Structural
equation modeling was selected as a
technique that was used to estimate,
analyze, and test the study model that
specified relationships among variables.
This allowed testing and validation
of already constructed theories
involving an evaluation of structure and
model fit. Semistructured interviews
were discovery-focused, which uncovered
contradictions and new ways of
thinking in the study model. This resulted
in the respecification of the structural
model variables and validation of
the accepted conceptual model. The
strength of structural coefficient paths
in the model needed assessment, as
goodness-of-fit measures do not provide
an absolute guarantee that each
particular part of the model fits well.
The structural model was evaluated by
modification indices that report the
improvement in fit that results from
adding or deleting an additional path to
the model. This introduced competing
models and the evaluation of individual
parameters. Modification indices results
suggested that model adjustments
would make no further improvements
to CMIN. Modifications also needed to
have substantive sense and theoretical
validation.
Model evaluation is one of the most
disputed and difficult issues connected
with structural modeling (Arbuckle,
2007). Structural equation models are
generally considered a good fit if the
value of the global model fit (CMIN
23.156, p 0.000) and badness of fit
index (RMSEA 0.248) test is adequate,
and at least one incremental fit index
(GFI 0.948) and one baseline fit measure
(NFI 0.900; IFI 0.912 and CFI
0.904) meet the predetermined criteria.
The study model satisfies and in some
cases exceeds this convention with the
exception of badness of fit index
(RMSEA). The minimum sample discrepancy
function (CMIN/DF) and
study sample size make RMSEA difficult
to interpret. This may be deceptive and
not necessarily indicate a poorly fitting
model. The structural model could be
considered adequate against prescribed
measures of fit providing a model that
conveys causal assumptions. The meaning
of “causal,” in this study, should be
interpreted with care, as structural equation
modeling does not confirm that
an accepted model produces validated
causal conclusions. The research
framework provided convergence and
Program governance
Systemic factors
Learning and innovation
Environment
Continuous alignment
Corporate strategy
e1
1
e2
1
e3
1
Successful delivery
e4
e5
e6
1
1
e7
1
1
Program design
e8
1
Figure 4: Statistically modified and theoretically validated model.
February 2012 ■ Project Management Journal ■ DOI: 10.1002/pmj 33
corroboration of findings resulting in
the statistically modified and theoretically
validated model. This was responsive
to changes in the unfolding of the
study. The study model was only partly
statistically tested due to insufficient
data, which revealed weaknesses in the
research design and methodology. These
were addressed to validate the structural
model and hypotheses before administrating
the test instrument to the wider
study population.
The qualitative research aspects of
the study design offered a richness and
depth of understanding unlikely to be
achieved with a stand-alone quantitative
approach. Some interesting underlying
issues, most notably relationships
among strategy, learning, and program
design, were exposed. There was reasonably
clear demonstration that
strategic vision was being translated
into programs. Program life-cycle phases
of design and transition were found
to be particularly problematic in practice
by interview respondents. This
emphasized that strategy was a rather
ambiguous phenomenon in practice.
The creation of strategy was seen to be
an easier process than implementation.
This reinforced that organizations were
complex systems. Strategic management
was principally perceived by
interview respondents as providing
required organizational direction in
dealing with success and failure from a
business context. There was recognition
that program success would not be
guaranteed even when a clearly articulated
business strategy was apparent
from the outset. Strategy was generally
seen to be emergent, affecting the program
as it moves down the organization.
There was recognition that
absolute organizational alignment may
be difficult and unrealistic as a consequence.
Interview respondents confirmed
that this made it necessary to
view programs as dynamic and evolving
structures.
The front-end of programs were
identified to be frequently ill defined,
with low levels of formation constraining
the early definition of success. This suggested
that program design and structure
was a dynamic process that needed
to be continually assessed from program
formation through to program
close. Interview respondents emphasized
that programs of projects should
continually use the best knowledge
obtainable to inform a systems view. In
their view, this was necessary to align
practice with stated goals. Other viewpoints
emphasized the need to move
away from the linear, milestone-based
processes of some business activities,
because integration was seen to go
hand-in-hand with experienced complexity.
The different practice-related
views of the interview respondents
demonstrated that in contextual detail
every program will be unique. This further
confirmed the presence of a high
level of execution-complexity with a
high level of organizational and environmental
complexity, since a wide
variety of variables need to be considered.
There was general consensus that
many organizations were not designed
for project management. Program
design was stated to be much more
complex than a static process. Practical
challenges were identified when the
host organization did not have the requisite
project management capability.
This further emphasized the highly
complex nature of effectively designing
programs of projects. Interview respondents
stated that program design was a
significantly important pre-implementation
activity. This led to its greater
prominence in the study model, as
inappropriate setup was seen as something
that would negatively impact
implementation and management of
the program. Interview respondents
suggested that programs need to be
designed to acknowledge the complexity
and emergent details of the program.
The study further exposed that program
culture was often underscored by
learning and innovation in responding
to inherent program complexity. This
strong underlying profile for learning
and knowledge-sharing practices was
occasionally underrated in the interview
phase of the study. There was
some evidence of systemic learning,
driven by a project management
approach, with people who had similar
levels of knowledge. Nonetheless, there
was a general tendency for learning to
be classified as a low priority. However,
the statistical model findings strongly
suggest that learning and innovation in
programs are fundamentally important
for success. The different types of learning
that emerged related less to structured
approaches and more to satisficing
and improvisational outcomes. There
was some recognition that increasing
program complexity will make organizational
learning a primary measure of
program management effectiveness.
Examples were given where program
learning had been effective but had
not been transferred to the wider
organization.
Conclusions
The selected model provides a conceptual
framework to support the understanding
of programs. The strength of
the model is in the illustration of the
systemic characteristics that will make
programs particularly challenging to
understand and manage. The hypothesized
statements can be conceived to be
a plausible set of interconnected narratives
that describe the relationships that
support the conceptualization of the
study model. This needs to include
the program design variable to allow
recursive feedback in the model. The
study model does highlight the importance
of effective program design and
transition management. The model
suggests that successful program delivery
will be an elusive concept in practice
that requires flexibility for strategic and
environmental adaptation.
The findings of the study conclude
that programs have both deliberate and
emergent strategies, requiring program
design and management to be organized
as complex adaptive systems. This
integrates theoretical concepts from
34 February 2012 ■ Project Management Journal ■ DOI: 10.1002/pmj
Successful Programs Wanted
PAPERS
systems thinking, organizational, and
project management theory. Complex
adaptive systems are often illustrated
by unclear strategies from the outset
and influential constant changes.
Interviewee knowledge of the concept
of complex adaptive systems was limited,
although descriptions and viewpoints
supported this system dynamic. Senior
managers and program managers need
to recognize the importance of all the
study model variables, how they align,
and the program capability required in
successfully delivering business strategy.
The adoption of program management
should thus be a well-considered
strategic decision.
This study contributes to program
management by the understanding of
complex adaptive systems and its application
to the project management field
in many ways. First, the study identified
several high-level variables that should
be considered to ensure the successful
alignment of programs. These variables
can be used to analyze project and program
failures contributing to organizational
learning. Second, the exploration
of these variables has led to the development
of a model that reveals an interaction
structure depicting program formation
and implementation in practice.
Finally, the results of validating the
study model have identified some of
the managerial problems that should be
considered when designing and managing
programs of projects.
Recommendations for Further
Research
Based on the literature review, study
results and emergent issues identified in
the study, there were some insights that
provide direction for future research. The
emergent reality of program management
requires a clearer understanding
on the impact of structured, incremental,
and contextual learning. Learning
within programs is also an identified gap
within the published literature. The
study also identified a significant need
to identify the effective practices and
approaches that support successful
program design. Research in this field
should consider how organizations
effectively apply an adaptive posture to
environmental factors.
Limitations
The study has a number of limitations.
Structural equation modeling cannot
test directionality in relationships. The
directions of arrows in the accepted
structural equation model represent the
researcher’s hypotheses of causality
within a program management system.
This is limited to the choice of selected
variables and hypothesized relation
pathways. Increasing the sample size
would improve the statistical model
convergence and parameter estimate
accuracy, providing greater confidence
in the model outcome. This may directly
affect the model path regression
weightings. The findings of the statistical
model are also influenced by the
researcher’s organization, which was
undergoing a significant organizationwide
change program. This potential
bias was adequately accounted for in
the selection strategy for the semistructured
interviews. Change programs are
vision-led and emergent. This puts
greater emphasis on culture change and
organizational readiness, which may
have enhanced the model path relationship
regression weightings for learning.
Every program classification will have
an inherent need to remain aligned with
business strategy, regardless of issues
relating to program context. ■
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Graeme Ritson is a construction lecturer at
Northumbria University. His background is in
construction and business-related projects. He
has 10 years of practical experience in managing
business improvement projects in a large
service organization.
Eric Johansen is the director of construction at
Northumbria University. After 20 years of project
management experience in the construction
industry, he became an academic in 1990. He
manages the Construction Group and teaches
and researches in lean construction, planning,
project, program, and portfolio management.
Allan Osborne is director of project management
at Northumbria University. He manages
the Project Management Group at the university
and teaches and researches in project team
dynamics and interorganizational relationships.
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