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COMPLEX THINKING AND THE PROJECT PORTFOLIO IN
PHILANTHROPIC HEALTH INSTITUTIONS
João Paulo de Sousa Silva1
Rafael Giacomassi2
Abstract: Working within a highly volatile scenario and subject to numerous interrelationships,
institutions in the philanthropic healthcare sector must navigate both the eciency and exibility,
characteristic of private entities, while retaining the focus on the purpose of social equity, typical of
public entities. This dichotomy renders the implementation of a project portfolio a signicant challenge.
It was in recognition of the inherent features of this scenario that this research grounded its development
in complex thinking. This allowed for learning rather than the imposition of pre-determinism, and
critical reection instead of hypothesis testing. Given the systemic nature of this research, the Soft
System Methodology was chosen as the approach. Conducted within a philanthropic institution
dedicated to oncological treatment, this unique case study originated from comprehending the
organizational context through the lens of complex thinking to formulate an action plan centered on the
implementation and management of a project portfolio. The outcomes demonstrated that steering this
process guided by complex thinking enables greater exibility and agility in project selection, as well
as enhanced integration among stakeholders, along with reduced maturation time in the initiation and
planning phases. On the other hand, this adoption opens discussions about the challenges of employing
a holistic line of thought within a culture rooted predominantly in the positivist paradigm.
Keywords: Complexity; Philanthropy; Oncological Healthcare; Systemic Thinking; Project Portfolio
1 Onshore Environmental Licensing Specialist
2 University of São Paulo [USP]. Master in Production Engineering
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Introduction
The interdependence between beings and the environment is no longer a simple epistemological
inquiry, nor does it constitute a new paradigm that needs validation. This more systemic logic extends
to organizational management, associating businesses no longer with machines, but with living beings.
Thus, its description advocates the identication and understanding of the relationships it maintains
with the actors and the environment in which it is inserted (Acko, 1999; Acko et al., 2006; Capra,
1982; Morin, Le Moigne, 1992; Ocelotl, 2021; Senge, 2017).
Through this more contextual bias, management must become more aware and responsive to
changes in the environment. These changes impact them at an increasingly accelerated pace, forcing
them to rethink both the way they understand themselves, their surroundings and interactions. As a
result, maximization and optimization give way to learning and purpose, problems become problem
situations and management becomes investigations (Kreher, 1995; Laloux, 2015; Serva, 1992).
Under this paradigm, the management of investments that translates into the project portfolio
must both incorporate knowledge that focuses on learning, rather than predicting the future, and
embrace the complexity of its context as a way to evolve and thrive (Laloux, 2017; Morecroft, Sterman,
1994; Wood Jr., 1993; Whitty and Maylor, 2009).
This understanding is based on the premises of complex thinking, which inserts aspects
previously considered problematic into the discussion of management. In this sense, their multiple
network interactions and uncertainties become functional premises, and errors or deviations are no
longer to be avoided (Barros et al, 2000; Laeur, 1996; Thamhain, 2013).
Therefore, the union between this school of thought and project management can be used
to better manage your investments, and your tools, techniques, and practices assertive options for
leadership in the health area (Brasil, 2023c; Ju Y, 2012; Sloane et al., 2003; Gomes et al.; 2003, Rhodes
et al., 2012).
The use of complex thinking in healthcare is becoming increasingly common. Several
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initiatives can be found, such as in the studies carried out by Lot (2023) that deals with the complexity
of networks, by Majeed et al (2023) that use it as a success factor, by Nason (2023) and Long et al (2018)
who directed their research to the diculties of its use, by Mahmoud et al (2022) who used it in the
decision-making process, and Colldén (2022) and its focus on contextual continuous improvement.
An important aspect in its use is the diculty of evaluating the impact and interaction
between multiple projects and the adoption of techniques that allow for a more agile maturation in the
face of sudden and unexpected changes, as a result of the high political inuence and the diculty in
raising resources typical of health (Berssaneti and Carvalho, 2015).
In line with these characteristics, this study demonstrates its relevance for its novelty in
applying the bases of complex thinking and project management to develop a portfolio of projects
in the area of philanthropic health, although there are initiatives of this alignment in other areas
(Aritua et al, 2008; Baccarini, 1996; Chapman, 2016; Tarhan, 2016; Checkland, 1972; Tomé et al,
2016; Thomas and Mengel, 2008).
Based on the above, the objective of this study is to analyze the impact of complex thinking
on the development and implementation of a portfolio of projects in the area of philanthropic health
from three aspects: multiple interactions, network dynamics and uncertainties.
Material and Methods
The research is characterized as exploratory and descriptive due to the need to approach the
subjects of the study, and the identication of more current research related to the topics addressed
(Gil, 1999; Vergara, 2005).
As for the methodology, it was guided by the “Soft System Methodology [SSM]” because
it is aligned with the constitutive premises of an Action Research [PA] and is the most recognized,
employed and cited. In addition, it allows both the evolution of the study guided by learning and the
focus on the generation of knowledge in contexts whose problem is not totally clear and dened,
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as well as the inclusion of new ideas after criticism, according to Checkland (1981), Checkland and
Poulter (2006), Mingers and Rosenhead (2004).
Consequently, a study that proposes a bias typical of complex thinking needs to use a
methodology developed under such premises at the risk of becoming biased if it is conducted by a
more reductionist one, Castellani and Rajaram (2021).
Its stages were developed through a cyclical process of planning, action and review,
where ideas are used in a methodology to study an area of interest, and where themes must replace
hypotheses. Thus, a structure of ideas [F] was incorporated into a methodology [M], to investigate
an area of Interest [A], whose dynamics changed the linear logic of validation of a hypothesis in
the more traditional molds of research, constituting much more as a continuous process of review
and improvement in the face of collected data, perceived interferences, interactions and unscheduled
changes, as advised by Checkland and Holwell (1998).
Consequently, the elements of investigation and the problem that this study sought to clarify,
as well as its stages of development, followed the cycles exposed in Figures 1 and 2 referenced below.
Figure 01: Initial elements of the investigation: theoretical basis
Source: Adapted from (CHECKLAND; HOLWELL, 1998)
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Figure 02: The project’s problem and its evolution and learning cycle
Source: Adapted from (Checkland and Holwell, 1998)
For data collection, internal documents were used, as well as research in articles and books and
on the websites of government regulatory agencies, as well as seminars and unstructured interviews
with the institution’s decision-makers in accordance with the premises of an AP (Thiollent, 1997).
In addition, cycles of criticism and review after each stage were carried out as a way to
consolidate knowledge along the lines proposed by Rau and Koch-Gonzalez (2018), as these data
collection techniques allow the inclusion of more subjective aspects when the use of determinisms
alone does not allow a clarication of their complexity (Checkland, Poulter, 2006).
As stages, this research presented:
STEP 1: Research plan and construction of the conceptual model
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As recommended for the learning cycle outlined for the research in Figure 2, the rst stage
consisted of the characterization of its context, already in the molds of SSM, as listed below.
The company that is the focus of the study and the philanthropic context
The institution in focus has been working in the area of philanthropic health for almost eight
decades with the challenge of combining high-standard oncological care with high accessibility.
In accordance with Law No. 12,101/2009, Brazil, (2009a), there is no xed or specic value
regarding the minimum percentage of free patient care. However, it is up to them to provide proof
of services at the minimum level of 60% aimed at the Unied Health System [SUS]. In addition,
the institution is recognized by the Ministry of Health as a “High Complexity Center in Oncology
[CACON]” and classied as a “Civil Society Organization of Public Interest [OSCIP]”.
This classication forces it to deal at the same time with eciency and exibility, typical
of private systems, without losing focus on the purpose of social equity, typical of public entities.
However, this duality is not consensual. Sectors of the government see the philanthropy typical of
large institutions as a mere artice to name the thing private, being, therefore, a mechanism to enjoy
tax benets while consolidating protable businesses in their services (Ribeiro, 1993).
As almost half of all health care in the country is provided through philanthropy, Brazil
(2021b), it was observed that, despite the legal classications, these organizations play a fundamental
role in maintaining the health system. This characterizes it as being typical of the third sector, that is,
one that has a symbiotic relationship between the public and the private (Paes, 2001).
The complex network of nancing its operations comes from various sources, mainly from
private initiatives, although there is undoubtedly participation of the state, either by directing funds
or by exempting fees and taxes. This reveals a dynamic where there are no guarantees, implying a
complicated game of interests for its managers and forcing it to base its investments not so much on
its strategy, but on the availability of funds and political interest (Weber, 1999; Coimbra, 1986).
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With regard to its capitalization, the charging of services to the portion of the population
that can aord it is not disregarded, thus combining voluntarism and business in a mix of practices
consistent with the characterization of Coimbra (1986). This charge has become a necessity for
survival, as the SUS transfer table has not been updated for more than twenty years, Brazil (2019c),
making it even more dicult to manage its operations.
Even in the face of these challenges, the company grew and included teaching and research
in its services. This form of broadening the scope of its functions took it out of the more spiritualist
and welfare bias of its foundation and characterized it more as focused on hospital medical care
(Ivamoto et al, 1998).
In view of the strong growth of recent years, the institution felt the need to structure its
portfolio of projects, starting a rst and failed attempt. This attempt whose main factor of friction
and stress was related to the incongruity of the choice of assumptions, techniques and deterministic
tools arising from the traditional management of predictive projects in an institution whose context
is characterized by extreme dynamics, subject to chaotic political and social inuences, and whose
strategic and operational culture was built by health professionals who did not necessarily have
knowledge about the premises of development of a complex project, therefore not even the inherent
needs for portfolio management.
After rethinking his strategy, a second attempt to implement a project oce and the
development of his portfolio began. This second initiative was outlined through this research.
Problem modeling
To contextualize both the problem context and the institution in relation to the philanthropic
health area, the CATWOE mnemonic was used, which is recommended by the SSM itself, and which
includes clients, actors, transformation, worldview, owner, and environmental restrictions (Checkland,
2000; Rose, 1997).
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As a way of enriching its use and lling possible gaps, such as a possible counterintuitive
rigidity in learning or the ambiguity of understanding the meaning of the terms (Checkland, 2000;
Bergvall-karenborn et al, 2004; Basden; Wood-Harper, 2006; Mingers, 1992), its use was based on
revisions that combine it with other techniques such as “strategic assumption surfacing and testing
[TAST]” and “critical systems thinking [CST]” (Bergvall-karenborn et al, 2004; Basden; Wood-
Harper, 2006) as a way of minimizing distortions of comprehension. Therefore, the mnemonic was
understood as:
• Customers: all those aected by the transformations (positively or negatively), with a
focus on those with the power to inuence;
• Actors: those responsible and with the competence to operationalize the transformations
(including the competences they lack);
• Transformation: inputs and outputs in terms of process, including auxiliary processes
related to the transformation;
• Worldview: multifaceted qualifying function that imprints meaning to transformation;
• Owner: those with the power to stop transformation, including aspects of dependencies
that hinder action;
• Environmental Restriction: elements that act as barriers, restricting the functioning of the
system (including legal, institutional and normative aspects – internal and/or external).
To facilitate and pacify the mnemonic information, a cycle of inuences was built whose
critical aspects were debated in rounds of arguments between those involved (board, infrastructure
and operations management) with the objective of both anticipating problems and minimizing risks
inherent to the implementation of the portfolio.
This cycle was built in accordance with the systemic understanding for problem situations
proposed by Senge (2017) and Acko (1999). In addition, its construction led to the constant exercise
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of monitoring dynamic forces, that is, interconnected patterns that shape the behavior and results of a
system over time and that inuence its results.
As the cultural factor demands an unpredictable time to present changes, the construction
of this cycle would allow those involved a shared criticism instead of pointing out the culprits in
moments of future resistance (Senge, 2017).
The choice of model for project management
Given the characteristics of the institution and the recommendation for the hybrid format
referenced by the Ministry of Health, Brazil (2023c), due to its inherent dynamics of systems whose
modeling language describes complex systems, these models allowed the construction of cause-eect
cycles to understand the critical interactions in projects and between projects, in addition to allowing
the understanding of diverse eects caused by various inuences, facilitating the management of
their activities (Forrester, 1961; Abdel-Hamid and Madnick, 1991).
Another aspect that corroborated the hybrid approach concerns the characteristics of the
projects developed at the institution. These projects involved multiple interrelated actors with a high
degree of dierentiation and interdependence (Baccarini, 1996); demanded a high capacity to respond
to change and a high focus on learning, Hass (2009); drawing on the experience of the actors involved,
Lima and Farias (2012); and involving multiple actors with diverse objectives, Davis, MacDonald, &
White (2010); in addition to demanding an approach that would unite several practices in favor of a
personalized and iterative model (Conforto et al, 2015).
That said, two maturity models were selected: the “Organizational Project Management
Maturity Model [OPM3]”, conceived and launched by the “Project Management Institute [PMI]” as a
progressive organizational maturity model developed from aggregated and interconnected knowledge
that focuses on three central domains: the project, the program or the portfolio (PMI, 2003); and
the “Adaptive Project Framework [APF]”, developed to allow adaptation to constant and uncertain
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changes in the scenario, with exibility for changes to the model itself, from the schedule, through the
budget, risks and planning stages in response to the characteristics of the project and the complexity
of the interactions that involve it (Wysocki, 2010, 2016).
Some factors justied the previous choice for OPM3 and APF:
• The FPA has a strong foundation in complex thinking, as it inserts uncertainties and
changes at the core of project management, making it an adaptive process in response
to the scenario to which the projects will be implemented, thus demonstrating total
alignment with the constitutive bases of this research and the focus institution (Wysocki,
2010);
• Developed from the organization’s need to rethink and standardize its processes, OPM3
forces the actors involved to delve into standardization before planning and executing
the project itself, according to PMI (2003). This direction proved to be fundamental for
the institution, as it was only in mid-2021 that the work of mapping and standardizing
its processes through “Lean” began, when the rst attempt to structure its project sector
also began;
• The existing projects, before the beginning of this research, mixed opportunities for
improvement that advocated the review and standardization of their operational
processes with others typical of more traditional and pre-deterministic projects, such as
renovation, construction and expansion of new units, therefore, not allowing a uniform
and standardized management;
• The cultural aspect of the institution and its resistance to a deterministic implementation
had already represented obstacles and generated stress among decision makers, making
the gradual implementation of “out of the box” knowledge (complex thinking and adaptive
systems applied to projects) a more palatable option;
• Finally, the typical exibility of these models allowed an alignment with the learning and
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evolution cycles recommended in Stage 1 (Figure 2).
Thus, from the consideration of these models, it would be possible to determine the maturity
phases and their deliverables, which through the choice of selection criteria would enable the selection
of the projects allocated in the portfolio in alignment with the investment demands.
Modeling the portfolio
The characterization of the maturity phases for the projects was followed by the prioritization
of opportunities. The objective was to guide the institution’s management in the argumentation and
debate with its funders, no longer guiding them solely by the political game of interests, but with
a view to more mature projects and less subject to risks, therefore, following more consistent and
technical criteria.
Among the various methods that characterize a “Multiple Criteria Decision Making
[MCDM]”, the “Analytical Hierarchy Process [AHP]” was chosen as the method to make this
prioritization possible. This choice is due to the ability to analyze complex problems under dierent
aspects, criteria and points of view, and to consider both objective and subjective preferences (Almeida,
2003; Bramont, 1996).
As variables for AHP, as advised by Saaty (1990, 2001), the following were suggested:
• Complexity: the scale proposed by the “Global Alliance for the Project Professions
[GAPPS]” was used, which through a simple sum of questions categorizes the complexity
of a project, (GAAPS, 2007). In it, ve factors were evaluated, whose variation translated
into 1 point (low inuence), 2 (medium inuence) and 3 (high inuence):
F1. Number and relevance of actors involved
F2. Number of variables and interactions
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F3. Technical, environmental and legal requirements
F4. Strategic importance of the project
F5. Financial impact
• Resources: subdivided into fully nanced (+90% of the estimated value), partially
nanced (between 90% and 70%) and unfunded (below 70%);
• Impact: divided into funding, improvement and liabilities, corresponding respectively
to projects that aim to increase revenue, improve operations or eliminate legal/labor
liabilities (regulatory adequacy).
• Care: related to the impact of the project on the supply and operationalization of the
service, subdivided into critical (impacts the perception of the patient/companion),
partially critical (impacts the operational activity, without direct reection on the patient)
and non-critical (when the impact does not impact either the operation or the patient).
The ranges of variation of these parameters were validated in cycles of criticism in seminars
with the main decision-makers of the board, operation and assistance. For each critical cycle, the AHP
was recalculated and the changes in priority were observed until there was neither a change in the
sequence of these parameters, nor an internal variation exceeding the range of 20% of the total (being
10% more or less).
It took three meetings for the sensitivity analysis process to meet the pre-dened standards.
Thus, existing projects could be categorized by their maturity and ranked based on technical criteria.
Tools for portfolio management
Two criteria were considered for the choice of the tools listed here: all should be associated
with the three characteristics determined in the objective of this study, and none of them should
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replace the parallel use of tools and techniques from the APF and OPR3 models, but should be
complementary to them.
As a theoretical framework for selecting these tools, the research used the Network Theory
due to its alignment with complex thinking and the possibility of using the internal inequalities inherent
to the network as benecial aspects to its evolution, in addition to allowing the insertion of new nodes,
leading to a dynamic component of connectivity that would allow its expansion (Barbarási, 2009).
In addition to these characteristics, robustness was also considered, that is, the ability to
withstand stress and overcome diculties without collapsing. Thus, the accumulation of advantages
dispersed among its nodes would lead the network to present clusters as a form of organization. This
clustering would minimize the spread of errors in the network and increase the eciency in the
exchange of information, since it would not be chaotic (long and random connections) enough for its
complexity to hinder its evolution, nor too rigid (short and crowded connections) to the point of stress
contaminating it completely (Barbarási, 2009; Staella and Lemos, 2010).
This understanding of networks allowed the selected techniques and tools to oer a more
contextual, non-linear and interactive view of the projects allocated in the portfolio, avoiding that they
were analyzed as isolated elements.
When the theory of networks encompasses the social factor, the Actor-Network Theory
has the possibility of conceiving the sociology (study of homogeneous) of associations (study
of heterogeneous). This led the study from the focus on the object, that is, on the product of the
project, to the focus on the associations that would allow its conclusion. The result would be the
understanding of the dynamics between the actors, enabling both the characterization, the evolution
and self-organization of the network necessary for the evolution of the projects (Latour, 2012; Staella
and Lemos, 2010).
Under this understanding, and in view of the determination of the deliverables for each phase
of maturation for the projects, it was possible to make network maps whose objective was to understand
the dynamics of informational exchange between the actors with decision-making power in relation
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to their development. In addition, it would be possible to standardize their responsibilities with these
actors, as well as to identify the informational ows for each phase of maturation, the occurrence of
the absence of imposed centralized control, the autonomous nature and high connectivity between
the subsystems, the non-linear causality, and an emerging decentralized control typical of complex
systems (Barbarási, 2009; Staella and Lemos, 2010; Kauman 1993).
In this sense, three networks were built. One focused on the interactions between the
functional nodes (sectors) involved in the maturation of projects (systems level), another detailing the
iterations between the deliverables of these nodes (subsystems level) and a last one focused on the
interrelationships between variables within a project (subcomponent level) so that there was a deeper
understanding of the portfolio interactions.
Finalizing the selection of tools, there was a need to evaluate the impact of the portfolio on
the institution’s operational centers. To this end, a Sankey Diagram was built where it was possible to
identify the increase in work, in the form of ow, from the closure of the projects in the portfolio, as
recommended by Riehmann et al. (2005), and which, associated with AHP, increased the assertiveness
in the selection of new projects, now in response to the anticipation of future bottlenecks in the
operational centers of the institution.
Figure 3 shows the construction logic used for the Sankey Diagram (Riehmann et al., 2005).
Figure 03: Sankey Diagram construction logic
Source: Adapted from (Riehmann et al., 2005)
Note: RDC-50 is a regulatory standard prepared by the Ministry of Health
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Finally, it would be necessary to select the software that would allow the management of
the portfolio. Thus, the use of Trello® and ClickUp were suggested®. The indication for these two
alternatives was based on the researcher’s experience of use and its inherent reduction in the learning
time required for implementation.
Based on the mapped tools, the following action plan was prepared.
Table 1. Action plan for Stage 2 and 3 of the survey
Source: Original survey data
SHARE DEFINITION HOW EXPECTED RESULT
Contextual Characterization Characterize inuences for
portfolio implementation
CATWOE Mnemonic
(SSM base)
Contextual features
Understand the critical inuences
for the portfolio
Systemic Cycle
(dynamic forces)
Dynamics of inuence in
portfolio management
Maturation Model Determination of ripening stages OPM3 and APF base Allocation of projects by
maturity stage
Determination of deliverables by
phase
OPM3 Base, APF and
Systemic Cycle
Stages and risks by
maturity stage
Management Tools Choice of management software Selecting between
Trello® and ClickUp®
Implementation of a
management system for
the portfolio
Prioritization criteria Application of AHP Standardization and
criteria
Understand inuence dynamics
between projects
Network map
(interactions)
Identify how projects
interact with each other
Understand informational
dynamics between actors involved
in the projects
Network map
(interactions)
Pacify among those
involved their
responsibilities and
inuences
Understand the dynamics of
inuence between maturation tools
Network map
(interactions)
Learn to optimize eorts
to increase results
Identify areas with demand
overload (future impact)
Sankey diagram Identify which functional
areas of the organization
are impacted
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STEPS 2 and 3: Practice and renement
Stages 2 and 3 following the development of the conceptual model for the portfolio and their
respective consolidation actions took place simultaneously. Some aspects justify this simultaneity:
• The organizational dynamics and the already mature projects did not allow a cadenced
implementation period typical of a more linear and sequential planning;
• Not all actions could be implemented to all projects due to their characteristics and
limitations.
Thus, these joint stages sought to identify which projects allocated in the portfolio would be
considered critical for the implementation of the plan (Table 1), and to determine how much this plan
would be deepened, since some of its actions required an implementation period longer than the time
of progress of the project already in the planning and execution phases.
STEP 4: Conclusion
The fourth and last stage of the research consisted of closing the SSM learning cycle and
presenting the results obtained.
Results and Discussion
The results of the research are shown in accordance with the chronological order in which
they were reached. Considerations about its results were made at the end of each stage in accordance
with the logic of criticism and learning of SSM.
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Contextual characterization
From the mnemonic provided for in the SSM, the inuencing factors for the research context
and for the implementation of the portfolio were identied, as shown in Table 2.
Table 2. Result for the CATWOE mnemonic
Source: Original survey results
Based on the information collected through unstructured interviews and seminars with
those involved, the mnemonic was modied to the format of a cycle of inuences. The operational
representative of the board, the infrastructure and assistance managers were involved.
Each round represented the contribution of an actor from their understanding of the connection
C
CLIENTS
Primary: SUS and Ministry of Health (funders), private initiative (funders), supplementary
patients (approx. 35% of care) and regulated patients (approx. 65% of care), public agencies
directing funds, state and national politicians, business development partners (research),
educational oer partners (teaching)
Secondary: students and professors in the health area, patient companions, outsourced and
volunteers of the institution, other oncological health institutions (state and national)
The
ACTORS
Primary: ocial public managers directly responsible for the operationalization of federal
public health policies, employees in the care area (including area managers and coordinators),
business partner physicians
Secondary: teachers and students, own sta, solution development partners, political
representatives with power of inuence (direct advisors), partner banks
T
TRANSFORMATION
MATION
Input: inuencing factors in the contextual dynamics of project nancing
Output: portfolio of projects (opportunities) with a minimum degree of maturity for
presentation in response to nancing alternatives
W
WORLDVIEW
Projects developed with the improvement of the experience of the patient and their families
through normative and legal services that guarantee service excellence
Or
OWNER
Primary: legislators and high-ranking members of the executive branch (state and federal
spheres), society (population served via SUS), business partner physicians
Secondary: society (supplementary population), health regulators
And
ENVIRONMENT
Primary: lag in the SUS table of services hinders capitalization, incongruence between
health standards (RDC family), public health policies (state and federal levels)
Secondary: inconstancy of public focus on health (changes associated with elections)
generating instability in the sector
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and sense of inuence of these factors, until a consensus was reached and a cohesive alignment was
achieved.
In the upper cycle, the reinforcements necessary to reach the study were listed and that,
through renement and continuous learning, would allow both the implementation and the evolution
of the project portfolio. This cycle represented not a linear sequence of inuence, but the systemic
logic that connects them (Senge, 2017). In the lower cycle, the factors that would act as detractors to
the objective were listed. This cycle was also built according to the dynamics of systems and their
learning models (Senge, 2017).
The analysis of these cycles represented the cultural context (factors) of positive and negative
inuence for the success of the research, and served as a reference for those involved to understand
that the desired results would only be possible if these factors were considered.
Considerations
The story told by the cycles, Figure 4, revealed which factors are critical to the implementation
of the portfolio. These factors should not be understood as causes in themselves, but as inuences that
demand attention and care in the face of each planned action. Therefore, there is no direct or causal
link from one to one, but from several to several, Capra (1982).
C
CLIENTS
Primary: SUS and Ministry of Health (funders), private initiative (funders), supplementary
patients (approx. 35% of care) and regulated patients (approx. 65% of care), public agencies
directing funds, state and national politicians, business development partners (research),
educational oer partners (teaching)
Secondary: students and professors in the health area, patient companions, outsourced and
volunteers of the institution, other oncological health institutions (state and national)
The
ACTORS
Primary: ocial public managers directly responsible for the operationalization of federal
public health policies, employees in the care area (including area managers and coordinators),
business partner physicians
Secondary: teachers and students, own sta, solution development partners, political
representatives with power of inuence (direct advisors), partner banks
T
TRANSFORMATION
MATION
Input: inuencing factors in the contextual dynamics of project nancing
Output: portfolio of projects (opportunities) with a minimum degree of maturity for
presentation in response to nancing alternatives
W
WORLDVIEW
Projects developed with the improvement of the experience of the patient and their families
through normative and legal services that guarantee service excellence
Or
OWNER
Primary: legislators and high-ranking members of the executive branch (state and federal
spheres), society (population served via SUS), business partner physicians
Secondary: society (supplementary population), health regulators
And
ENVIRONMENT
Primary: lag in the SUS table of services hinders capitalization, incongruence between
health standards (RDC family), public health policies (state and federal levels)
Secondary: inconstancy of public focus on health (changes associated with elections)
generating instability in the sector
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Figure 04: Systemic cycle (reinforcement and compensation)
Source: Original survey results
Maturity model and its deliverables
Immediately after the denition of the cycle, there was a period of study regarding the
OPM3 and APF models that resulted in the determination of the maturity phases, and their respective
deliverables, for the institution’s project portfolio. It should be noted that none of these models were
fully followed, but considered as a basis for the development of a hybrid model that was more assertive
to the reality of the institution.
As it is a more technical process, only the researcher, the director and the operational manager
participated in this methodological comparison.
The result of this analysis is shown in Table 3 below.
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Table 3. Maturity phases and phased deliverables for projects
Source: Original survey results
NOTE: *Number of projects considered active allocated to each phase
As there is no standardization of nomenclature between OPM3 and APF, the concordances
between the two models were analyzed with regard to: approach to the maturity phases, gain of
experience throughout the evolution of the project; gradual evolution as a premise for increasing
value; and the possibility of fractional deliveries (agility).
PHASE DELIVERABLE QNT*
DEMAND D1. Project Charter: Denition of scope + objectives + goals + systemic
interactions
D2. Estimated area (m²)
D3. Classication and prioritization of the project in the portfolio (AHP)
D4: Estimated costs per m² (only work)
D5: Estimated time and execution stages
35
INITIATION I1: Zoning and architectural pre-design
I2: Impact estimation (scope) + changes
I3: Review of cost estimation (includes acquisitions)
I4: Identication of legal documentation
I5: Identication of complementary projects
14
PLANNING P1: Reaction plan (changes)
P2: Architectural and complementary executive design
P3: Operational opening plan (commissioning)
P4: Procurement plan
P5: Breakdown structure (when applicable)
P6: Docs. legal (opening of cases
5
EXECUTION E1: Impact monitoring (scope) + changes
E2: Architectural executive project
E3: Opening plan
E4: Procurement plan
E5: Legal documents (processes)
E6: Complementary executive projects
21
CLOSURE N1: As-built projects
N2: Data book (equip. and building)
N3: Term of delivery
N5: Indicators + Settlement
4
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This denition made it possible to allocate existing projects within a standardized maturation
logic, which did not exist before, in addition to allowing those involved a glimpse of their roles and
obligations in each phase. It also allowed the development of the rst draft of the project portfolio for
the institution and the measurement of the eorts necessary for the continuity of its activities, which
had been stopped since the pause in the implementation of the project oce.
Considerations
Although it was not the focus of this study, the macroow of actions was restructured for
the evolution of the projects in respect to the dened maturation phases. This delineation of steps was
fundamental for the future construction of network maps.
Consequently, the basic structure of the portfolio was selected, the management system. This
selection was scheduled for a future moment in the research plan, however, it was requested by the
board of directors to implement it ahead of schedule as a way of disseminating and facilitating access
to information. Thus, due to the researcher’s previous knowledge, ClickUp® was the system selected,
and as soon as implemented, loaded with basic information and about the projects in their respective
maturation phase.
However, it was observed that the necessary and subsequent prioritization activity for
the projects could not be extrapolated to all phases, being restricted to the projects allocated in the
Demand phase. This restriction made it possible for the projects allocated in the following stages not
to have their execution order changed in view of the new criterion, which would imply sudden and
costly changes in work and increased costs.
This denition implied a radical change with the management regarding its position in
relation to the continuity of investments. Historically, there was a change in the destination of funds,
even in mature projects, hindering their execution and paralyzing them, with a consequent increase in
operating costs. The repositioning was positive, as the project oce can, from this moment on, plan,
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execute and nalize projects already started before a new initiative.
Prioritization criteria for projects
Consequently the allocation of projects and according to the denitions of the maturation
phases, the denition of the prioritization criteria for the portfolio began. These criteria were presented
and settled with the directors of the institution through three stages:
• Denition of the hierarchical structure with criteria and alternatives by level;
• Comparison of alternatives, pairing and sensitivity analysis;
• Normalization, weight calculations and prioritization of projects in the portfolio.
The results of the sensitivity analysis for the dened parameters were, respectively: Impact
(48%), Resources (30%), Assistance (15%) and Complexity (7%).
Based on these variables, the projects in the demand phase were ranked.
Considerations
Despite the initial results, some factors pointed out as detractors in the systemic cycle proved
to be critical and present, impacting the totality of the use of AHP.
A culture consolidated for more than seven decades would not suddenly change, even in the
face of the consensual adoption of validated techniques. The consolidation of variables as criteria
for analysis and prioritization came up against the inherent diculty of changing the posture in the
dynamics of investment selection.
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Complex network maps
In alignment with the Network Theory, groupings, or nodes, were identied that allowed
us to understand how the demands for projects were aligned with the organizational strategy. There
was also the consolidation of the ow of information necessary for its maintenance, as well as the
identication of the risks related to each stage. These interactions led to the self-regulation of the
system, i.e. the integrity of the portfolio.
Thus, instead of determining risks mapped in the linear format of cause and eect, there was
an understanding of how disturbances in the network inuenced the portfolio. The focus, therefore,
shifted from the control of variables to the management of inuences, which began to be analyzed
in terms of disturbance, the impact of which generated uncertain and chaotic emergent states that
demanded greater or lesser attention.
While Figure 5 reveals the dynamics that associate the demand for projects with the institution’s
strategy, making it possible to understand the system of inuences that connects them (organizational
sectors involved), Figures 6 and 7 reveal the functional nodes and their macro network of interaction
and informational ows (subsystems and critical components, whose product was characterized as a
deliverable to the project).
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Figure 5: Strategic network map for the demand for projects (systems)
Source: Original survey results
Figure 6: Network map and cluster identication (subsystems)
Source: Original survey results
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Figure 7: Breakdown of the network for portfolio management (subsystems and components)
Source: Original survey results
These maps made it possible to see impacts on a multilevel scale, making it possible to see
which deliverables would be harmed if a problem was noticed in a given node. Special attention
is paid to the NLH - Hospital Licensing Center, a decit node given its newly dened operational
premise regarding the survey of legal and normative documentation that must be met by the projects.
This same logic of network analysis became part of the development for projects whose
evaluation by the GAPPS premises achieved the highest scores. Thus, these projects had their nodes
mapped so that their critical interactions could be evaluated by those involved (designers and managers)
in their maturation (evolution and risks).
Figure 8 reveals the map of interactions of the Access Control component of Project X based
on the disciplines involved in the complementary projects contracted.
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Figure 8: Operational interaction map for the “accesses” node in project x
Source: Original survey results
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Considerations
Because it is easier to understand which words, relational gures are more eective in
transmitting ideas, as Checkland (2000) and Acko (2017) attest. This use, recommended by SSM
and Network Theory, proved to be fundamental for the institution to absorb premises of complex
thinking in a more organic way.
The construction of these maps only for complex projects does not contradict the result of
the prioritization and criteria listed by AHP. The level of complexity, even conguring low inuence
as a selection criterion, did not eliminate its observance in some projects, since AHP ranked projects
in terms of gains. That said, a project may not be ranked as a priority by AHP, but require a network
analysis in its maturation stages due to the GAPPS classication.
Identifying areas impacted by projects
After the implementation of the network maps for the projects qualied as complex, the
research proceeded with the identication and ranking of the functional areas that would be impacted
in a given time window.
By determination of the operational board, a two-year window was considered.
All projects were evaluated in relation to the following question: this project will cause an
increase in service in which areas? If a certain operational area was impacted, grade one would be
assigned to it. If not, the score zero.
In a seminar with the participation of the operational board, and assistance and engineering
management, all the projects allocated in the portfolio were evaluated in relation to the aforementioned
issue. The sum of points awarded allowed the construction of the Sankey Diagram.
This diagram did not assess the intensity of the impact, since this assessment required criteria,
ow analyses and specic operational capacities that could only be eective when the projects were
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closed and their gains validated (status indicators). However, there was an assessment of whether
this impact occurred. Aware that intensity could drastically alter the ranking, the development of
the diagram would only make it possible to identify which areas would be overloaded as the projects
allocated in the portfolio were completed.
This diagram, therefore, was considered as an additional secondary information whose
objective was to allow us to see the increase in services in the functional centers of the institution and
to guide the realization of more detailed studies by the continuous improvement and controllership
sector, responsible for the feasibility studies.
Figure 9 shows the Sankey Diagram elaborated for the project portfolio. In it, highlighted
in red, it is possible to identify the project causing the greatest impact, followed respectively by the
second, in orange, and third, in yellow. The other projects did not present impacts considered relevant
by those involved, although their evaluation contributed to the formulation of the diagram.
Figure 9: Sankey diagram for complex projects allocated in the portfolio
Source: Original survey results
Note: The name of some projects has been withheld for condentiality
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Considerations
The use of the Sankey Diagram enabled an unprecedented analysis for the institution’s
decision-makers, because, even if the intensity of the impact was not included, its preparation
represented an unprecedented alignment of visions, based on the expertise of the operational and
strategic sta. Thus, its elaboration shed light on which functional nuclei, until then considered
secondary and normally ignored, would undergo an increase in their services.
End-of-results analysis
The analysis proposed by the objective of this study was carried out based on the three
aspects listed, highlighting the following results:
Regarding the use of complex thinking:
• Identication of critical stakeholders to the projects in the form of systemic maps
facilitated the understanding and importance of adopting complex thinking;
• Greater understanding of the dependencies between those involved who were able to
visualize the impacts of their actions on the mapped network;
• Greater management over decit nodes, including their communication channels, as a
way to minimize risks related to the critical information ow to projects;
• Increase of more than 350% in the number of projects in execution in the portfolio,
related to the implementation of the maturation ow and determination of deliverables;
• Reduction of 44% in the time dedicated to the preparation of architectural projects,
which were directed more assertively from the maturation of the project (prerequisite
engineering) and no longer as the start of the development process;
• Reduction of 35.2% in the preparation time of complementary projects, from the holding
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of seminars with designers with the objective of listing impacts between their disciplines.
When observing the adoption of network maps, it was possible to list:
• Understanding of the interdependencies that impact management, maturation and risks
linked to projects;
• Network map for architecture made standard for complex projects allowed to identify
risk areas with greater agility;
• Improvement of the process of raising demands between actors, based on the crossing of
impacts and needs (added value);
• Assertiveness rate between planned (planning) and validated (execution) budgets with an
average variation of 12.5%, as a result of the mapping actions and identication of critical
interactions and their respective actions to mitigate systemic risks.
Regarding the uncertainties:
• Interdisciplinary collaboration based on the joint elaboration of scenarios reduced
uncertainties and risks;
• The association between the Network Map and the Sankey Chart made it possible
to evaluate the impact on secondary areas where decisions were previously made by
impressions. An example of this gain was the indication of new projects for the area
of nutrition, sterilization center and hospitality, in response to the expansion of units
(service capacity – service provided);
• Maturation phases and interaction between deliverables streamlined decision-making, in
response to the perception of systemic critical risks (network).
When observing the number of actions planned for the research, it was noted that all of them
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were implemented, however, only a quantitative analysis proved to be supercial. This superciality
is related to restrictions regarding its scope, that is, the impossibility of applying these actions in all
the projects that constituted the portfolio analyzed.
This incongruity was due to the fact that, although the selection of techniques and tools
demonstrated convergence with the objective of the study, their characteristics did not make total
sense when observing the characteristics of some projects already under development in the portfolio.
Only projects identied as complex and allocated in the demand and planning phases had all
the actions listed in the plan carried out. However, in relation to the nancial amount, the percentage
corresponded to seventy-ve percent of all allocated resources. This percentage included all critical
projects (high added value and monetary investment). This reveals and reiterated the need to include
qualitative aspects for the research, since only the quantitative bias would reduce the impact of the
work developed.
Regarding the tools and techniques presented, the ClickUp® software, as well as the network
diagrams, have become standard for exposure and evaluation in the weekly meetings with the board.
Limitations and suggestions for future work
The adoption of SSM as a methodology required the research to constantly review and
expand the recommended data collection, since such action requires the identication concomitant
with the execution of its execution stages (adaptive process). This represented an unestimated increase
in time for the collection of the data necessary for the research and a redoubled eort so that the nal
objective of the research did not go out of focus.
As the study was limited to using complex thinking in the implementation of an institution’s
portfolio of projects in the area of philanthropic health, generalizations to other areas of health may
represent bias, since the dynamics of inuence for funding and inuence of the actors involved for
their projects can vary considerably. However, the choice for SSM demonstrated alignment with this
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reality, since its learning cycle is contextual, that is, developed in a personalized way for each use.
That said, even with perceptible benecial results, the following are pointed out as restrictions
observed in the implementation of the dened action plan:
• The use of AHP in unison with the Sankey Diagram required a review of process
improvement assumptions and the adoption of tools outside the scope of the research that
contradicted some improvement strategies adopted (use of Lean);
• The cadenced follow-up of the stages of maturation of the projects by phases (deliverables)
in association with the network maps (risks and systemic impacts) revealed operational
gaps that minimized the expected gains for these tools and techniques. However, as
predicted by the cycle of inuences in Figure 4, the conclusion of this research was
an opportunity to include specic training in the institution’s leadership development
programs for the coming cycle;
• Another limiting aspect was related to time, because, even though this work lasted
for a period of almost a year, the adaptation of the language and techniques typical of
complex thinking required dedicated time that was only possible due to the commitment
of management to its implementation. This barrier can be easily referenced by Senge
(2017) and Acko (1999), who mention the need for periods of awareness regarding the
impact of this adoption on the organizational culture so that some tools can be minimally
understood.
For future works, the inclusion of other actors in the construction of the research plan is
indicated, since their involvement is crucial to pacify concepts and minimize risks related to the
noise of understanding this current of thought, which advocates the breaking of paradigms typical of
mechanistic thinking.
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Final Thoughts
The adoption of complex thinking represented a paradigmatic change in the researcher’s
professional journey, as a view based on the incorporation of factors previously understood as avoidable
as a rule for the development of actions required openness to knowledge previously ignored. However,
this adoption has expanded the capacity to deal with these aspects and facilitated the identication
of qualitative impacts where previously there was a translation of reality based only on a quantitative
bias.
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